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Ni Z, Bousquet C, Vaillant P, Jaulent MC. Rapid Review on Publicly Available Datasets for Health Misinformation Detection. Stud Health Technol Inform 2023; 305:123-126. [PMID: 37386973 DOI: 10.3233/shti230439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Abstract
The proliferation of health misinformation in recent years has prompted the development of various methods for detecting and combatting this issue. This review aims to provide an overview of the implementation strategies and characteristics of publicly available datasets that can be used for health misinformation detection. Since 2020, a large number of such datasets have emerged, half of which are focused on COVID-19. Most of the datasets are based on fact-checkable websites, while only a few are annotated by experts. Furthermore, some datasets provide additional information such as social engagement and explanations, which can be utilized to study the spread of misinformation. Overall, these datasets offer a valuable resource for researchers working to combat the spread and consequences of health misinformation.
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Affiliation(s)
- Zhenni Ni
- School of Information Management, Wuhan University, Wuhan, China
- Sorbonne Université, UMR_S 1142, LIMICS, Paris, France
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2
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Dimitsaki S, Natsiavas P, Jaulent MC. Transfer Learning for Early Prediction of Adverse Drug Reactions: Docetaxel and Alopecia in Breast Cancer as a Case Study. Stud Health Technol Inform 2023; 302:396-397. [PMID: 37203703 DOI: 10.3233/shti230158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Transfer Learning (TL) is an approach which has not yet been widely investigated in healthcare, mostly applied in image data. This study outlines a TL pipeline leveraging Individual Case Safety reports (ICSRs) and Electronic Health Records (EHR), applied for the early detection Adverse Drug Reactions (ADR), evaluated using of alopecia and docetaxel on breast cancer patients as use case.
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Affiliation(s)
- Stella Dimitsaki
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la eSanté, LIMICS, F-75006 Paris, France
- Institute of Applied Biosciences, Centre for Research and Development Hellas, Thessaloniki, Greece
| | - Pantelis Natsiavas
- Institute of Applied Biosciences, Centre for Research and Development Hellas, Thessaloniki, Greece
| | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la eSanté, LIMICS, F-75006 Paris, France
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3
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von Tottleben M, Grinyer K, Arfa A, Traore L, Verdoy D, Lim Choi Keung SN, Larranaga I, Jaulent MC, De Manuel Keenoy E, Lilja M, Beach M, Marguerie C, Yuksel M, Laleci Erturkmen GB, Klein GO, Lindman P, Mar J, Kalra D, Arvanitis TN. An Integrated Care Platform System (C3-Cloud) for Care Planning, Decision Support, and Empowerment of Patients With Multimorbidity: Protocol for a Technology Trial. JMIR Res Protoc 2022; 11:e21994. [PMID: 35830239 PMCID: PMC9330187 DOI: 10.2196/21994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 12/18/2020] [Accepted: 10/02/2021] [Indexed: 11/16/2022] Open
Abstract
Background There is an increasing need to organize the care around the patient and not the disease, while considering the complex realities of multiple physical and psychosocial conditions, and polypharmacy. Integrated patient-centered care delivery platforms have been developed for both patients and clinicians. These platforms could provide a promising way to achieve a collaborative environment that improves the provision of integrated care for patients via enhanced information and communication technology solutions for semiautomated clinical decision support. Objective The Collaborative Care and Cure Cloud project (C3-Cloud) has developed 2 collaborative computer platforms for patients and members of the multidisciplinary team (MDT) and deployed these in 3 different European settings. The objective of this study is to pilot test the platforms and evaluate their impact on patients with 2 or more chronic conditions (diabetes mellitus type 2, heart failure, kidney failure, depression), their informal caregivers, health care professionals, and, to some extent, health care systems. Methods This paper describes the protocol for conducting an evaluation of user experience, acceptability, and usefulness of the platforms. For this, 2 “testing and evaluation” phases have been defined, involving multiple qualitative methods (focus groups and surveys) and advanced impact modeling (predictive modeling and cost-benefit analysis). Patients and health care professionals were identified and recruited from 3 partnering regions in Spain, Sweden, and the United Kingdom via electronic health record screening. Results The technology trial in this 4-year funded project (2016-2020) concluded in April 2020. The pilot technology trial for evaluation phases 3 and 4 was launched in November 2019 and carried out until April 2020. Data collection for these phases is completed with promising results on platform acceptance and socioeconomic impact. We believe that the phased, iterative approach taken is useful as it involves relevant stakeholders at crucial stages in the platform development and allows for a sound user acceptance assessment of the final product. Conclusions Patients with multiple chronic conditions often experience shortcomings in the care they receive. It is hoped that personalized care plan platforms for patients and collaboration platforms for members of MDTs can help tackle the specific challenges of clinical guideline reconciliation for patients with multimorbidity and improve the management of polypharmacy. The initial evaluative phases have indicated promising results of platform usability. Results of phases 3 and 4 were methodologically useful, yet limited due to the COVID-19 pandemic. Trial Registration ClinicalTrials.gov NCT03834207; https://clinicaltrials.gov/ct2/show/NCT03834207 International Registered Report Identifier (IRRID) RR1-10.2196/21994
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Affiliation(s)
- Malte von Tottleben
- empirica Gesellschaft für Kommunikations- und Technologieforschung mbH, Bonn, Germany
| | - Katie Grinyer
- empirica Gesellschaft für Kommunikations- und Technologieforschung mbH, Bonn, Germany
| | - Ali Arfa
- empirica Gesellschaft für Kommunikations- und Technologieforschung mbH, Bonn, Germany
| | - Lamine Traore
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Inserm, Sorbonne Université, Université Paris 13, Paris, France
| | - Dolores Verdoy
- Kronikgune Institute for Health Services Research, Barakaldo, Spain
| | - Sarah N Lim Choi Keung
- Institute of Digital Healthcare (IDH), Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
| | - Igor Larranaga
- Kronikgune Institute for Health Services Research, Barakaldo, Spain.,Basque Health Service (Osakidetza), Debagoiena Integrated Healthcare Organisation, Research Unit, Arrasate-Mondragón, Guipúzcoa, Spain
| | - Marie-Christine Jaulent
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Inserm, Sorbonne Université, Université Paris 13, Paris, France
| | | | - Mikael Lilja
- Unit of Research, Education, and Development Östersund, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Marie Beach
- South Warwickshire University NHS Foundation Trust, Warwick, United Kingdom
| | | | - Mustafa Yuksel
- Software Research Development and Consultancy Cooperation, SRDC A.S., Ankara, Turkey
| | | | - Gunnar O Klein
- School of Business (Informatics), Örebro University, Örebro, Sweden
| | | | - Javier Mar
- Basque Health Service (Osakidetza), Debagoiena Integrated Healthcare Organisation, Research Unit, Arrasate-Mondragón, Guipúzcoa, Spain
| | | | | | - Theodoros N Arvanitis
- Institute of Digital Healthcare (IDH), Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom
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4
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Agher D, Sedki K, Despres S, Albinet JP, Jaulent MC, Tsopra R. Encouraging Behavior Changes and Preventing Cardiovascular Diseases Using the Prevent Connect Mobile Health App: Conception and Evaluation of App Quality. J Med Internet Res 2022; 24:e25384. [PMID: 35049508 PMCID: PMC8814926 DOI: 10.2196/25384] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 03/04/2021] [Accepted: 04/25/2021] [Indexed: 12/18/2022] Open
Abstract
Background Cardiovascular diseases are a major cause of death worldwide. Mobile health apps could help in preventing cardiovascular diseases by improving modifiable risk factors such as eating habits, physical activity levels, and alcohol or tobacco consumption. Objective The aim of this study was to design a mobile health app, Prevent Connect, and to assess its quality for (1) assessing patient behavior for 4 cardiovascular risk factors (unhealthy eating, sedentary lifestyle, alcohol, and tobacco consumption) and (2) suggesting personalized recommendations and mobile health interventions for risky behaviors. Methods The knowledge base of the app is based on French national recommendations for healthy eating, physical activity, and limiting alcohol and tobacco consumption. It contains a list of patient behaviors and related personalized recommendations and digital health interventions. The interface was designed according to usability principles. Its quality was assessed by a panel of 52 users in a 5-step process: completion of the demographic form, visualization of a short presentation of the app, testing of the app, completion of the user version of the Mobile App Rating Scale (uMARS), and an open group discussion. Results This app assesses patient behaviors through specific questionnaires about 4 risk factors (unhealthy eating, sedentary lifestyle, alcohol, and tobacco consumption) and suggests personalized recommendations and digital health interventions for improving behavior. The app was deemed to be of good quality, with a mean uMARS quality score of 4 on a 5-point Likert scale. The functionality and information content of the app were particularly appreciated, with a mean uMARS score above 4. Almost all the study participants appreciated the navigation system and found the app easy to use. More than three-quarters of the study participants found the app content relevant, concise, and comprehensive. The aesthetics and the engagement of the app were also appreciated (uMARS score, 3.7). Overall, 80% (42/52) of the study participants declared that the app helped them to become aware of the importance of addressing health behavior, and 65% (34/52) said that the app helped motivate them to change lifestyle habits. Conclusions The app assessed the risky behaviors of the patients and delivered personalized recommendations and digital health interventions for multiple risk factors. The quality of the app was considered to be good, but the impact of the app on behavior changes is yet to be demonstrated and will be assessed in further studies.
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Affiliation(s)
- Dahbia Agher
- Inserm, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
- BeWellConnect Research and Development, Visiomed Group, Puteaux, France
| | - Karima Sedki
- Inserm, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Sylvie Despres
- Inserm, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | | | - Marie-Christine Jaulent
- Inserm, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Rosy Tsopra
- Inserm, Université de Paris, Sorbonne Université, Centre de Recherche des Cordeliers, F-75006, Paris, France
- HEKA, Inria, Paris, France
- Department of Medical Informatics, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
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Gavriilidis GI, Dimitriadis VK, Jaulent MC, Natsiavas P. Identifying Actionability as a Key Factor for the Adoption of 'Intelligent' Systems for Drug Safety: Lessons Learned from a User-Centred Design Approach. Drug Saf 2021; 44:1165-1178. [PMID: 34674190 PMCID: PMC8553681 DOI: 10.1007/s40264-021-01103-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/18/2021] [Indexed: 12/02/2022]
Abstract
Introduction Information technology (IT) plays an important role in the healthcare landscape via the increasing digitization of medical data and the use of modern computational paradigms such as machine learning (ML) and knowledge graphs (KGs). These ‘intelligent’ technical paradigms provide a new digital ‘toolkit’ supporting drug safety and healthcare processes, including ‘active pharmacovigilance’. While these technical paradigms are promising, intelligent systems (ISs) are not yet widely adopted by pharmacovigilance (PV) stakeholders, namely the pharma industry, academia/research community, drug safety monitoring organizations, regulatory authorities, and healthcare institutions. The limitations obscuring the integration of ISs into PV activities are multifaceted, involving technical, legal and medical hurdles, and thus require further elucidation. Objective We dissect the abovementioned limitations by describing the lessons learned during the design and implementation of the PVClinical platform, a web platform aiming to support the investigation of potential adverse drug reactions (ADRs), emphasizing the use of knowledge engineering (KE) as its main technical paradigm. Results To this end, we elaborate on the related ‘business processes’ (i.e. operational processes) and ‘user goals’ identified as part of the PVClinical platform design process based on Design Thinking principles. We also elaborate on key challenges restricting the adoption of such ISs and their integration in the clinical setting and beyond. Conclusions We highlight the fact that beyond providing analytics and useful statistics to the end user, ‘actionability’ has emerged as the operational priority identified through the whole process. Furthermore, we focus on the needs for valid, reproducible, explainable and human-interpretable results, stressing the need to emphasize on usability.
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Affiliation(s)
- George I. Gavriilidis
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, 6th Km. Charilaou, Thermi Road, PO Box 60361, 57001 Thermi, Thessaloniki Greece
| | - Vlasios K. Dimitriadis
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, 6th Km. Charilaou, Thermi Road, PO Box 60361, 57001 Thermi, Thessaloniki Greece
| | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d’Informatique Médicale et d’Ingénierie des Connaissances pour la e-Santé, LIMICS, 75006 Paris, France
| | - Pantelis Natsiavas
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, 6th Km. Charilaou, Thermi Road, PO Box 60361, 57001 Thermi, Thessaloniki Greece
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d’Informatique Médicale et d’Ingénierie des Connaissances pour la e-Santé, LIMICS, 75006 Paris, France
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6
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Allam N, Audeh B, Jaulent MC, Bousquet C. Visualising Patterns Associated with Adverse Drug Reactions in French Forums. Stud Health Technol Inform 2021; 281:1110-1111. [PMID: 34042861 DOI: 10.3233/shti210368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
As social media are an interesting source of information for pharmacovigilance, we implemented a novel visualisation method for pharmacovigilance specialists applied to French discussion forums. A word embedding model was trained on posts to facilitate the identification of patterns associated with adverse drug reactions.
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Affiliation(s)
- Nour Allam
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
- ESIEE Paris graduate school of engineering, Noisy-le-Grand, France
| | - Bissan Audeh
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Cedric Bousquet
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
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7
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Agher D, Sedki K, Tsopra R, Despres S, Jaulent MC. Influence of Connected Health Interventions for Adherence to Cardiovascular Disease Prevention: A Scoping Review. Appl Clin Inform 2020; 11:544-555. [PMID: 32814353 DOI: 10.1055/s-0040-1715649] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022] Open
Abstract
BACKGROUND Recent health care developments include connected health interventions to improve chronic disease management and/or promote actions reducing aggravating risk factors for conditions such as cardiovascular diseases. Adherence is one of the main challenges for ensuring the correct use of connected health interventions over time. OBJECTIVE This scoping review deals with the connected health interventions used in interventional studies, describing the ways in which these interventions and their functions effectively help patients to deal with cardiovascular risk factors over time, in their own environments. The objective is to acquire knowledge and highlight current trends in this field, which is currently both productive and immature. METHODS A structured literature review was constructed from Medline-indexed journals in PubMed. We established inclusion criteria relating to three dimensions (cardiovascular risk factors, connected health interventions, and level of adherence). Our initial search yielded 98 articles; 78 were retained after screening on the basis of title and abstract, 49 articles underwent full-text screening, and 24 were finally retained for the analysis, according to preestablished inclusion criteria. We excluded studies of invasive interventions and studies not dealing with digital health. We extracted a description of the connected health interventions from data for the population or end users. RESULTS We performed a synthetic analysis of outcomes, based on the distribution of bibliometrics, and identified several connected health interventions and main characteristics affecting adherence. Our analysis focused on three types of user action: to read, to do, and to connect. Finally, we extracted current trends in characteristics: connect, adherence, and influence. CONCLUSION Connected health interventions for prevention are unlikely to affect outcomes significantly unless other characteristics and user preferences are considered. Future studies should aim to determine which connected health design combinations are the most effective for supporting long-term changes in behavior and for preventing cardiovascular disease risks.
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Affiliation(s)
- Dahbia Agher
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France.,BeWellConnect, Research and Development, Visiomed Group 75016 Paris, France
| | - Karima Sedki
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Rosy Tsopra
- INSERM, Université Paris Descartes, Sorbonne Université, Centre de Recherche des Cordeliers, Information Sciences to support Personalized Medicine, F-75006 Paris, France.,Department of Medical Informatics, H⊚pital Européen Georges-Pompidou, AP-HP, Paris, France
| | - Sylvie Despres
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Marie-Christine Jaulent
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
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8
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Natsiavas P, Gavriilidis GI, Linardaki Z, Kolangi G, Gkaliagkousi E, Zamboulis C, Jaulent MC. Supporting Active Pharmacovigilance via IT Tools in the Clinical Setting and Beyond: Regulatory and Management Aspects. Stud Health Technol Inform 2020; 272:342-345. [PMID: 32604672 DOI: 10.3233/shti200565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Information Technology (IT) could have a prominent role towards the "Active Pharmacovigilance" (AP) paradigm by facilitating the analysis of potential Adverse Drug Reactions (ADRs). PVClinical project aims to build an IT platform enabling the investigation of potential ADRs in the clinical environment and beyond. In this paper, we outline the respective EU regulatory framework and the related Business Processes (BPs), elaborated based on input from clinicians and PV experts as part of the project's "user requirements analysis" phase, highlighting their potential pivotal role in the design of IT tools aiming to support AP.
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Affiliation(s)
- Pantelis Natsiavas
- Institute of Applied Biosciences, Centre for Research & Technology Hellas, Thermi, Thessaloniki, Greece
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75006 Paris, France
| | - George I Gavriilidis
- Institute of Applied Biosciences, Centre for Research & Technology Hellas, Thermi, Thessaloniki, Greece
| | | | | | - Evgenia Gkaliagkousi
- 3rd Department of Internal Medicine, Papageorgiou Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75006 Paris, France
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9
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Agher D, Fouque M, Brandi M, Sedki K, Tsopra R, Meneton P, Despres S, Jaulent MC. Decision Support System for Selection of e-Health Interventions. Stud Health Technol Inform 2020; 272:326-329. [PMID: 32604668 DOI: 10.3233/shti200561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The main goal of this work was to design a decision support system for effective personalized cardiovascular risk prevention: i) to identify behavioral groups associated with clinical risk factors, ii) to provide recommendations associated with the objective to be achieved and iii) to determine the decision-making rules assigning each group to the type of mobile health intervention conveying the most appropriate prevention messages, to help patients to achieve attainable goals. The system is based on an existing data prediction model taking into account specific risky behaviors, clinical risk factors and social status, and it is embedded in a new e-health application. The system is operational. The next step will be the design of a large study to assess improvements in patient adherence to prevention messages through e-health interventions selected by the application.
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Affiliation(s)
- Dahbia Agher
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
- BeWellConnect, 75116 Paris, France
| | - Marc Fouque
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Matteo Brandi
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Karima Sedki
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Rosy Tsopra
- INSERM, Centre de Recherche des Cordeliers, UMRS 1138, Université Paris-Descartes, Université Sorbonne Paris Cité, France
- Department of Medical Informatics, Hospital European Georges-Pompidou, AP-HP, Paris, France
| | - Pierre Meneton
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Sylvie Despres
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
| | - Marie-Christine Jaulent
- INSERM, University Sorbonne Paris Nord, Sorbonne University, Laboratory of Medical Informatics and Knowledge Engineering in e-Health, LIMICS, Paris, France
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10
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Chauvet R, Bousquet C, Lillo-Lelouet A, Zana I, Ben Kimoun I, Jaulent MC. Classification of the Severity of Adverse Drugs Reactions. Stud Health Technol Inform 2020; 270:1227-1228. [PMID: 32570592 DOI: 10.3233/shti200375] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
This poster presents a non-exhaustive study of machine learning classification algorithms on pharmacovigilance data. In this study, we have taken into account the patient's clinical data such as medical history, medications taken and their indications for prescriptions, and the observed side effects. From these elements we determine whether the patient case is considered serious or not. We show the performances of the different algorithms by their precision, recall and accuracy as well as their learning curves.
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Affiliation(s)
- Raphaël Chauvet
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France.,EISTI, International Engineering School, 95000 Cergy-Pontoise, France
| | - Cédric Bousquet
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Agnès Lillo-Lelouet
- Centre Régional de Pharmacovigilance, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Ilan Zana
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Ilan Ben Kimoun
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
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11
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Despotou G, Laleci Erturkmen GB, Yuksel M, Sarigul B, Lindman P, Jaulent MC, Bouaud J, Traore L, Lim Choi Keung SN, De Manuel E, Verdoy D, De Blas A, Gonzalez N, Lilja M, Sherman M, Von Tottleben M, Beach M, Marguerie C, Karni L, Klein GO, Kalra D, Chen R, Arvanitis TN. Localisation, Personalisation and Delivery of Best Practice Guidelines on an Integrated Care and Cure Cloud Architecture: The C3-Cloud Approach to Managing Multimorbidity. Stud Health Technol Inform 2020; 270:623-627. [PMID: 32570458 DOI: 10.3233/shti200235] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND C3-Cloud is an integrated care ICT infrastructure offering seamless patient-centered approach to managing multimorbidity, deployed in three European pilot sites. Challenge: The digital delivery of best practice guidelines unified for multimorbidity, customized to local practice, offering the capability to improve patient personalization and benefit. METHOD C3-Cloud has adopted a co-production approach to developing unified multimorbidity guidelines, by collating and reconciling best practice guidelines for each condition. Clinical and technical teams at pilot sites and the C3-Cloud consortium worked in tandem to create the specification and technical implementation. RESULTS C3-Cloud offers CDSS for diabetes, renal failure, depression and congenital heart failure, with over 300 rules and checks that deliver four best practice guidelines in parallel, customized for each pilot site. CONCLUSIONS The process provided a traceable, maintainable and audited digitally delivered collated and reconciled guidelines.
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Affiliation(s)
- George Despotou
- Institute of Digital Healthcare, WMG, University of Warwick, Coventry, UK
| | | | - Mustafa Yuksel
- SRDC Software Research Development and Consultancy Corp, Ankara, Turkey
| | - Bunyamin Sarigul
- SRDC Software Research Development and Consultancy Corp, Ankara, Turkey
| | | | | | - Jacques Bouaud
- Inserm, Sorbonne University, University of Paris 13, LIMICS, France.,AP-HP, Delegation for Clinical Research and Innovation, Paris
| | - Lamine Traore
- Inserm, Sorbonne University, University of Paris 13, LIMICS, France
| | | | | | - Dolores Verdoy
- Kronikgune, Institute for Health Services Research, Spain
| | | | | | - Mikael Lilja
- Department of Public Health and Clinical Medicine, Unit of Research, Education, and Development Östersund Hospital, Umeå University, Umeå, Sweden
| | | | | | | | | | - Liran Karni
- Örebro University School of Business, Informatics, Örebro, Sweden
| | - Gunnar O Klein
- Örebro University School of Business, Informatics, Örebro, Sweden
| | - Dipak Kalra
- European Institute for Innovation through Health Data, Belgium
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12
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Beuscart R, Bouaud J, Jaulent MC, Séroussi B. Vassilis Koutkias (1975 - 2019) - the Painful Loss of a Rare Person. Yearb Med Inform 2020. [DOI: 10.1055/s-0040-1701982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022] Open
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13
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Bousquet C, Souvignet J, Sadou É, Jaulent MC, Declerck G. Ontological and Non-Ontological Resources for Associating Medical Dictionary for Regulatory Activities Terms to SNOMED Clinical Terms With Semantic Properties. Front Pharmacol 2019; 10:975. [PMID: 31551780 PMCID: PMC6747929 DOI: 10.3389/fphar.2019.00975] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 07/31/2019] [Indexed: 11/20/2022] Open
Abstract
Background: Formal definitions allow selecting terms (e.g., identifying all terms related to “Infectious disease” using the query “has causative agent organism”) and terminological reasoning (e.g., “hepatitis B” is a “hepatitis” and is an “infectious disease”). However, the standard international terminology Medical Dictionary for Regulatory Activities (MedDRA) used for coding adverse drug reactions in pharmacovigilance databases does not beneficiate from such formal definitions. Our objective was to evaluate the potential of reuse of ontological and non-ontological resources for generating such definitions for MedDRA. Methods: We developed several methods that collectively allow a semiautomatic semantic enrichment of MedDRA: 1) using MedDRA-to-SNOMED Clinical Terms (SNOMED CT) mappings (available in the Unified Medical Language System metathesaurus or other mapping resources, e.g., the MedDRA preferred term “hepatitis B” is associated to the SNOMED CT concept “type B viral hepatitis”) to extract term definitions (e.g., “hepatitis B” is associated with the following properties: has finding site liver structure, has associated morphology inflammation morphology, and has causative agent hepatitis B virus); 2) using MedDRA labels and lexical/syntactic methods for automatic decomposition of complex MedDRA terms (e.g., the MedDRA systems organ class “blood and lymphatic system disorders” is decomposed in blood system disorders and lymphatic system disorders) or automatic suggestions of properties (e.g., the string “cyclic” in preferred term “cyclic neutropenia” leads to the property has clinical course cyclic). Results: The Unified Medical Language System metathesaurus was the main ontological resource reusable for generating formal definitions for MedDRA terms. The non-ontological resources (another mapping resource provided by Nadkarni and Darer in 2010 and MedDRA labels) allowed defining few additional preferred terms. While the Ci4SeR tool helped the curator to define 1,935 terms by suggesting potential supplemental relations based on the parents’ and siblings’ semantic definition, defining manually all MedDRA terms remains expensive in time. Discussion: Several ontological and non-ontological resources are available for associating MedDRA terms to SNOMED CT concepts with semantic properties, but providing manual definitions is still necessary. The ontology of adverse events is a possible alternative but does not cover all MedDRA terms either. Perspectives are to implement more efficient techniques to find more logical relations between SNOMED CT and MedDRA in an automated way.
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Affiliation(s)
- Cédric Bousquet
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, LIMICS, Sorbonne Université, Inserm, Université Paris 13, Paris, France.,Unit of Public Health and Medical Informatics, University of Saint Etienne, Saint Etienne, France
| | - Julien Souvignet
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, LIMICS, Sorbonne Université, Inserm, Université Paris 13, Paris, France.,Unit of Public Health and Medical Informatics, University of Saint Etienne, Saint Etienne, France
| | - Éric Sadou
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, LIMICS, Sorbonne Université, Inserm, Université Paris 13, Paris, France
| | - Marie-Christine Jaulent
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, LIMICS, Sorbonne Université, Inserm, Université Paris 13, Paris, France
| | - Gunnar Declerck
- EA 2223 Costech (Connaissance, Organisation et Systèmes Techniques), Centre de Recherche, Sorbonne Universités, Université de technologie de Compiègne, Compiègne, France
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14
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Natsiavas P, Jaulent MC, Koutkias V. A Knowledge-Based Platform for Assessing Potential Adverse Drug Reactions at the Point of Care: User Requirements and Design. Stud Health Technol Inform 2019; 264:1007-1011. [PMID: 31438076 DOI: 10.3233/shti190376] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Even though Adverse Drug Reactions (ADRs) constitute a significant public health issue, there is a lack of Information & Communication Technologies (ICT) tools supporting Pharmacovigilance activities at the point of care. In this paper, we present the rationale of a Web-based platform to address this need. The driving user scenario of the proposed platform refers to a clinician who investigates information for a possible ADR as part of a specific patient treatment. The goal is to facilitate this assessment through appropriate tools for searching various relevant data sources, analysing the acquired data, aggregating the obtained evidence, and offering follow-up ADR monitoring over time in a systematic and user-friendly way. In this regard, we describe the adopted user requirements engineering methodology and illustrate the use of Knowledge Engineering (KE) as the platform's main technical paradigm to enable heterogeneous data integration and handle the complexity of the underlying information processing workflow.
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Affiliation(s)
- Pantelis Natsiavas
- Institute of Applied Biosciences, Centre for Research & Technology Hellas, Thermi, Thessaloniki, Greece.,Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75006 Paris, France
| | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75006 Paris, France
| | - Vassilis Koutkias
- Institute of Applied Biosciences, Centre for Research & Technology Hellas, Thermi, Thessaloniki, Greece
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15
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Pelayo S, Schiro J, Gautier PF, Jaulent MC, Marcilly R. User Driven Design: First Step in Involving Healthcare Consumers and Clinicians in Developing a Collaborative Platform to Prevent Cardiovascular Diseases. Stud Health Technol Inform 2019; 264:1313-1317. [PMID: 31438138 DOI: 10.3233/shti190439] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
To prevent cardiovascular diseases, eHealth solutions may be used as tools, involving health care consumers in the set-up of their prevention plan, a fundamental condition for improving their long-term adherence to the plan. This paper presents the first step in a web platform design aiming to support the co-elaboration by health care consumers and clinicians of personalized prevention plans. Applying a user driven innovation approach, first, a questionnaire and semi-structured interviews were combined to identify clinicians' needs. Then, three focus group sessions with consumers and clinicians were organized to identify their needs, creating the system workflows, its graphical user interface, and its navigation paths, with the best ideas shaped by paper mockups. An interactive mockup was designed including 30 screens (ex. user dashboards, desk for co-elaborating plan). This user driven approach enabled to design not only the technology and its graphical user interface, but also a prevention plan design process.
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Affiliation(s)
- Sylvia Pelayo
- Univ. Lille, INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation Clinique, EA 2694, F-59000 Lille, France
| | - Jessica Schiro
- Univ. Lille, INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation Clinique, EA 2694, F-59000 Lille, France
| | - Pierre-François Gautier
- Univ. Lille, INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation Clinique, EA 2694, F-59000 Lille, France
| | | | - Romaric Marcilly
- Univ. Lille, INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation Clinique, EA 2694, F-59000 Lille, France
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16
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Shi H, Pfaender F, Jaulent MC. Mapping the Hyperlink Structure of Diabetes Online Communities. Stud Health Technol Inform 2019; 264:467-471. [PMID: 31437967 DOI: 10.3233/shti190265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Diabetes is one of the largest global health emergencies of the 21st century. As a chronic disease, diabetes requires continuous medical care and constant patient self-management. Such care involves several stakeholders to improve health outcome and patient quality of life. This paper makes use of World Wide Web network analysis to highlight how stakeholders, providing information about online diabetes communities, link to each other. To achieve this, we capture the network of diabetes related websites as a digital trace of a non-digital phenomenon. Furthermore, this helps us to understand the current situation of diabetes organizations from a digital perspective. The methodology involves state-of-the-art tools to crawl (Hyphe) and visualize (Gephi) topic-sensitive networks. While neither of these tools is new in itself, their combination provides a promising way to analyze chronic disease stakeholders, organizations and communities, representing a large proportion of the knowledge and support diabetes patients have access to nowadays.
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Affiliation(s)
- Hongyi Shi
- INSERM, UMR_S 1142, LIMICS, F-75006, Paris, France
- Sorbonne Université, Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France
- Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Fabien Pfaender
- Fabien Pfaender, UTSEUS, Shanghai University, Shanghai, China
- Costech EA2223, Université de Technologie de Compiègne, Compiègne, France
| | - Marie-Christine Jaulent
- INSERM, UMR_S 1142, LIMICS, F-75006, Paris, France
- Sorbonne Université, Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France
- Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
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17
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Traore L, Assele-Kama A, Keung SNLC, Karni L, Klein GO, Lilja M, Scandurra I, Verdoy D, Yuksel M, Arvanitis TN, Tsopra R, Jaulent MC. User-Centered Design of the C3-Cloud Platform for Elderly with Multiple Diseases - Functional Requirements and Application Testing. Stud Health Technol Inform 2019; 264:843-847. [PMID: 31438043 DOI: 10.3233/shti190342] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The number of patients with multimorbidity has been steadily increasing in the modern aging societies. The European C3-Cloud project provides a multidisciplinary and patient-centered "Collaborative Care and Cure-system" for the management of elderly with multimorbidity, enabling continuous coordination of care activities between multidisciplinary care teams (MDTs), patients and informal caregivers (ICG). In this study various components of the infrastructure were tested to fulfill the functional requirements and the entire system was subjected to an early application testing involving different groups of end-users. MDTs from participating European regions were involved in requirement elicitation and test formulation, resulting in 57 questions, distributed via an internet platform to 48 test participants (22 MDTs, 26 patients) from three pilot sites. The results indicate a high level of satisfaction with all components. Early testing also provided feedback for technical improvement of the entire system, and the paper points out useful evaluation methods.
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Affiliation(s)
- Lamine Traore
- Inserm, Sorbonne Université, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75011 Paris, France
| | - Ariane Assele-Kama
- Inserm, Sorbonne Université, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75011 Paris, France
| | | | - Liran Karni
- Örebro University School of Business, Informatics, Örebro, Sweden
| | - Gunnar O Klein
- Örebro University School of Business, Informatics, Örebro, Sweden
| | - Mikael Lilja
- Department of Public Health and Clinical Medicine, Unit of Research, Education, and Development Östersund Hospital, Umeå University, Umeå, Sweden
| | | | - Dolores Verdoy
- Asociacion Centro De Excelencia Internacional En Investigacion Sobre Cronicidad - Kronikgune, Spain
| | - Mustafa Yuksel
- SRDC Software Research Development & Consultancy Corp, Ankara, Turkey
| | | | - Rosy Tsopra
- Inserm, Sorbonne Université, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75011 Paris, France.,AP-HP, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Marie-Christine Jaulent
- Inserm, Sorbonne Université, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, F-75011 Paris, France
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18
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Natsiavas P, Malousi A, Bousquet C, Jaulent MC, Koutkias V. Computational Advances in Drug Safety: Systematic and Mapping Review of Knowledge Engineering Based Approaches. Front Pharmacol 2019; 10:415. [PMID: 31156424 PMCID: PMC6533857 DOI: 10.3389/fphar.2019.00415] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Accepted: 04/02/2019] [Indexed: 12/12/2022] Open
Abstract
Drug Safety (DS) is a domain with significant public health and social impact. Knowledge Engineering (KE) is the Computer Science discipline elaborating on methods and tools for developing “knowledge-intensive” systems, depending on a conceptual “knowledge” schema and some kind of “reasoning” process. The present systematic and mapping review aims to investigate KE-based approaches employed for DS and highlight the introduced added value as well as trends and possible gaps in the domain. Journal articles published between 2006 and 2017 were retrieved from PubMed/MEDLINE and Web of Science® (873 in total) and filtered based on a comprehensive set of inclusion/exclusion criteria. The 80 finally selected articles were reviewed on full-text, while the mapping process relied on a set of concrete criteria (concerning specific KE and DS core activities, special DS topics, employed data sources, reference ontologies/terminologies, and computational methods, etc.). The analysis results are publicly available as online interactive analytics graphs. The review clearly depicted increased use of KE approaches for DS. The collected data illustrate the use of KE for various DS aspects, such as Adverse Drug Event (ADE) information collection, detection, and assessment. Moreover, the quantified analysis of using KE for the respective DS core activities highlighted room for intensifying research on KE for ADE monitoring, prevention and reporting. Finally, the assessed use of the various data sources for DS special topics demonstrated extensive use of dominant data sources for DS surveillance, i.e., Spontaneous Reporting Systems, but also increasing interest in the use of emerging data sources, e.g., observational healthcare databases, biochemical/genetic databases, and social media. Various exemplar applications were identified with promising results, e.g., improvement in Adverse Drug Reaction (ADR) prediction, detection of drug interactions, and novel ADE profiles related with specific mechanisms of action, etc. Nevertheless, since the reviewed studies mostly concerned proof-of-concept implementations, more intense research is required to increase the maturity level that is necessary for KE approaches to reach routine DS practice. In conclusion, we argue that efficiently addressing DS data analytics and management challenges requires the introduction of high-throughput KE-based methods for effective knowledge discovery and management, resulting ultimately, in the establishment of a continuous learning DS system.
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Affiliation(s)
- Pantelis Natsiavas
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece.,Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France
| | - Andigoni Malousi
- Laboratory of Biological Chemistry, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Cédric Bousquet
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France.,Public Health and Medical Information Unit, University Hospital of Saint-Etienne, Saint-Étienne, France
| | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Univ Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances pour la e-Santé, LIMICS, Paris, France
| | - Vassilis Koutkias
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
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19
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Souvignet J, Declerck G, Trombert-Paviot B, Asfari H, Jaulent MC, Bousquet C. Semantic Queries Expedite MedDRA Terms Selection Thanks to a Dedicated User Interface: A Pilot Study on Five Medical Conditions. Front Pharmacol 2019; 10:50. [PMID: 30792654 PMCID: PMC6374626 DOI: 10.3389/fphar.2019.00050] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 01/16/2019] [Indexed: 11/13/2022] Open
Abstract
Background: Searching into the MedDRA terminology is usually limited to a hierarchical search, and/or a string search. Our objective was to compare user performances when using a new kind of user interface enabling semantic queries versus classical methods, and evaluating term selection improvement in MedDRA. Methods: We implemented a forms-based web interface: OntoADR Query Tools (OQT). It relies on OntoADR, a formal resource describing MedDRA terms using SNOMED CT concepts and corresponding semantic relations, enabling terminological reasoning. We then compared time spent on five examples of medical conditions using OQT or the MedDRA web-based browser (MWB), and precision and recall of the term selection. Results: OntoADR Query Tools allows the user to search in MedDRA: One may enter search criteria by selecting one semantic property from a dropdown list and one or more SNOMED CT concepts related to the range of the chosen property. The user is assisted in building his query: he can add criteria and combine them. Then, the interface displays the set of MedDRA terms matching the query. Meanwhile, on average, the time spent on OQT (about 4 min 30 s) is significantly lower (−35%; p < 0.001) than time spent on MWB (about 7 min). The results of the System Usability Scale (SUS) gave a score of 62.19 for OQT (rated as good). We also demonstrated increased precision (+27%; p = 0.01) and recall (+34%; p = 0.02). Computed “performance” (correct terms found per minute) is more than three times better with OQT than with MWB. Discussion: This pilot study establishes the feasibility of our approach based on our initial assumption: performing MedDRA queries on the five selected medical conditions, using terminological reasoning, expedites term selection, and improves search capabilities for pharmacovigilance end users. Evaluation with a larger number of users and medical conditions are required in order to establish if OQT is appropriate for the needs of different user profiles, and to check if conclusions can be extended to other kinds of medical conditions. The application is currently limited by the non-exhaustive coverage of MedDRA by OntoADR, but nevertheless shows good performance which encourages continuing in the same direction.
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Affiliation(s)
- Julien Souvignet
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, INSERM, Sorbonne Université, Université Paris 13, Paris, France
| | - Gunnar Declerck
- EA 2223 Costech (Connaissance, Organisation et Systèmes Techniques), Centre de Recherche, Sorbonne Universités, Université de Technologie de Compiègne, Compiègne, France
| | - Béatrice Trombert-Paviot
- Public Health and Medical Information Unit, University Hospital of Saint-Etienne, Saint-Étienne, France
| | - Hadyl Asfari
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, INSERM, Sorbonne Université, Université Paris 13, Paris, France
| | - Marie-Christine Jaulent
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, INSERM, Sorbonne Université, Université Paris 13, Paris, France
| | - Cédric Bousquet
- Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, INSERM, Sorbonne Université, Université Paris 13, Paris, France.,Public Health and Medical Information Unit, University Hospital of Saint-Etienne, Saint-Étienne, France
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20
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Miñarro-Giménez JA, Cornet R, Jaulent MC, Dewenter H, Thun S, Gøeg KR, Karlsson D, Schulz S. Quantitative analysis of manual annotation of clinical text samples. Int J Med Inform 2018; 123:37-48. [PMID: 30654902 DOI: 10.1016/j.ijmedinf.2018.12.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Revised: 10/09/2018] [Accepted: 12/30/2018] [Indexed: 11/18/2022]
Abstract
BACKGROUND Semantic interoperability of eHealth services within and across countries has been the main topic in several research projects. It is a key consideration for the European Commission to overcome the complexity of making different health information systems work together. This paper describes a study within the EU-funded project ASSESS CT, which focuses on assessing the potential of SNOMED CT as core reference terminology for semantic interoperability at European level. OBJECTIVE This paper presents a quantitative analysis of the results obtained in ASSESS CT to determine the fitness of SNOMED CT for semantic interoperability. METHODS The quantitative analysis consists of concept coverage, term coverage and inter-annotator agreement analysis of the annotation experiments related to six European languages (English, Swedish, French, Dutch, German and Finnish) and three scenarios: (i) ADOPT, where only SNOMED CT was used by the annotators; (ii) ALTERNATIVE, where a fixed set of terminologies from UMLS, excluding SNOMED CT, was used; and (iii) ABSTAIN, where any terminologies available in the current national infrastructure of the annotators' country were used. For each language and each scenario, we configured the different terminology settings of the annotation experiments. RESULTS There was a positive correlation between the number of concepts in each terminology setting and their concept and term coverage values. Inter-annotator agreement is low, irrespective of the terminology setting. CONCLUSIONS No significant differences were found between the analyses for the three scenarios, but availability of SNOMED CT for the assessed language is associated with increased concept coverage. Terminology setting size and concept and term coverage correlate positively up to a limit where more concepts do not significantly impact the coverage values. The results did not confirm the hypothesis of an inverse correlation between concept coverage and IAA due to a lower amount of choices available. The overall low IAA results pose a challenge for interoperability and indicate the need for further research to assess whether consistent terminology implementation is possible across Europe, e.g., improving term coverage by adding localized versions of the selected terminologies, analysing causes of low inter-annotator agreement, and improving tooling and guidance for annotators. The much lower term coverage for the Swedish version of SNOMED CT compared to English together with the similarly high concept coverage obtained with English and Swedish SNOMED CT reflects its relevance as a hub to connect user interface terminologies and serving a variety of user needs.
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Affiliation(s)
- Jose A Miñarro-Giménez
- Institute of Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria.
| | - Ronald Cornet
- Department of Medical Informatics, Amsterdam Public Health Research Institute, The Netherlands
| | - M C Jaulent
- Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en eSanté, Institut National de la Santé et de la Recherche Médicale, Sorbonne Université, Université Paris 13, France
| | - Heike Dewenter
- University of Applied Sciences Niederrhein, Krefeld, Germany
| | - Sylvia Thun
- Charité Universitätsmedizin, Berlin Institute of Health, Germany
| | | | - Daniel Karlsson
- Department for Knowledge-Based Policy of Social Services, eHealth and Structured Information Unit, The National Board of Health and Welfare, Sweden
| | - Stefan Schulz
- Institute of Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria
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21
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Maaroufi M, Landais P, Messiaen C, Jaulent MC, Choquet R. Federating patients identities: the case of rare diseases. Orphanet J Rare Dis 2018; 13:199. [PMID: 30419918 PMCID: PMC6233538 DOI: 10.1186/s13023-018-0948-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 10/30/2018] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Patient information in rare disease registries is generally collected from numerous data sources, necessitating the data to be federated. In addition, data for research purposes must be de-identified. Transforming nominative data into de-identified data is thus a key issue, while minimizing the number of identity duplicates. We propose a method enabling patient identity federation and rare disease data de-identification while preserving the pertinence of the provided data. RESULTS We developed a rare disease patient identifier. The IdMR generation process is a three-phased algorithm involving a hash function to irreversibly de-identify nominative patient data, including those of foetuses. This process minimizes collision risks and reduces variability for the purpose of identity federation. The IdMR was generated for 360,000 patients of the CEMARA database. It allowed identity federation of 1771 duplicated files. No collisions were introduced. CONCLUSION We examined and discussed the risks of collisions and the creation of duplicates as well as the risks of patient re-identification. We discussed our choice of nominative input information in light of that used by other patient identification solutions. The IdMR is a patient identifier that enables identity federation and file linkage. The simplicity of the algorithm and the universality and stability of the input data make it a good candidate for European cross-border rare disease projects.
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Affiliation(s)
- Meriem Maaroufi
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France.,INSERM, U1142, and UMR_S 1142, LIMICS, Sorbonne University, Paris, France.,Pierre and Marie Curie University, Paris, France.,Paris 13 University, F-93430, Villetaneuse, France
| | - Paul Landais
- UPRES EA2415, Clinical Research University Institute, Montpellier University, 641 avenue du Doyen Gaston Giraud, 34093, Montpellier, France. .,INSERM UMRS 933, Rare Disease Cohorts (RaDiCo), Sorbonne University, and Hôpital Trousseau, Assistance Publique Hôpitaux de Paris, Paris, France.
| | - Claude Messiaen
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Marie-Christine Jaulent
- INSERM, U1142, and UMR_S 1142, LIMICS, Sorbonne University, Paris, France.,Pierre and Marie Curie University, Paris, France.,Paris 13 University, F-93430, Villetaneuse, France
| | - Rémy Choquet
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France.,INSERM, U1142, and UMR_S 1142, LIMICS, Sorbonne University, Paris, France.,Pierre and Marie Curie University, Paris, France.,Paris 13 University, F-93430, Villetaneuse, France
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22
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Lardon J, Bellet F, Aboukhamis R, Asfari H, Souvignet J, Jaulent MC, Beyens MN, Lillo-LeLouët A, Bousquet C. Evaluating Twitter as a complementary data source for pharmacovigilance. Expert Opin Drug Saf 2018; 17:763-774. [DOI: 10.1080/14740338.2018.1499724] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Affiliation(s)
- Jérémy Lardon
- Sorbonne Université, UPMC Université Paris 06, UMR_S 1142, LIMICS, Paris, France
- INSERM, U1142, LIMICS, Paris, France
- Université Paris 13, Sorbonne Paris Cité, LIMICS (UMR_S 1142), Bobigny, France
- Department of Public Health and medical informatics, CHU University of Saint-Etienne, Saint-Etienne, France
| | - Florelle Bellet
- Centre de Pharmacovigilance, Centre Hospitalier Universitaire (CHU) University Hospital of Saint-Etienne, Saint-Etienne, France
| | - Rim Aboukhamis
- Centre Régional de Pharmacovigilance, Hôpital Européen Georges Pompidou – Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Hadyl Asfari
- Sorbonne Université, UPMC Université Paris 06, UMR_S 1142, LIMICS, Paris, France
- INSERM, U1142, LIMICS, Paris, France
| | - Julien Souvignet
- Sorbonne Université, UPMC Université Paris 06, UMR_S 1142, LIMICS, Paris, France
- INSERM, U1142, LIMICS, Paris, France
- Université Paris 13, Sorbonne Paris Cité, LIMICS (UMR_S 1142), Bobigny, France
- Department of Public Health and medical informatics, CHU University of Saint-Etienne, Saint-Etienne, France
| | - Marie-Christine Jaulent
- Sorbonne Université, UPMC Université Paris 06, UMR_S 1142, LIMICS, Paris, France
- INSERM, U1142, LIMICS, Paris, France
- Université Paris 13, Sorbonne Paris Cité, LIMICS (UMR_S 1142), Bobigny, France
| | - Marie-Noëlle Beyens
- Centre de Pharmacovigilance, Centre Hospitalier Universitaire (CHU) University Hospital of Saint-Etienne, Saint-Etienne, France
| | - Agnès Lillo-LeLouët
- Centre Régional de Pharmacovigilance, Hôpital Européen Georges Pompidou – Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Cédric Bousquet
- Sorbonne Université, UPMC Université Paris 06, UMR_S 1142, LIMICS, Paris, France
- INSERM, U1142, LIMICS, Paris, France
- Université Paris 13, Sorbonne Paris Cité, LIMICS (UMR_S 1142), Bobigny, France
- Department of Public Health and medical informatics, CHU University of Saint-Etienne, Saint-Etienne, France
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Jaulent MC, Leprovost D, Charlet J, Choquet R. Semantic interoperability challenges to process large amount of data perspectives in forensic and legal medicine. J Forensic Leg Med 2018; 57:19-23. [PMID: 29801946 DOI: 10.1016/j.jflm.2016.10.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Revised: 10/06/2016] [Accepted: 10/07/2016] [Indexed: 10/20/2022]
Abstract
This article is a position paper dealing with semantic interoperability challenges. It addresses the Variety and Veracity dimensions when integrating, sharing and reusing large amount of heterogeneous data for data analysis and decision making applications in the healthcare domain. Many issues are raised by the necessity to conform Big Data to interoperability standards. We discuss how semantics can contribute to the improvement of information sharing and address the problem of data mediation with domain ontologies. We then introduce the main steps for building domain ontologies as they could be implemented in the context of Forensic and Legal medicine. We conclude with a particular emphasis on the current limitations in standardisation and the importance of knowledge formalization.
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Affiliation(s)
- Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France.
| | - Damien Leprovost
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France
| | - Jean Charlet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France; AP-HP, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Remy Choquet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France; BNDMR, Assistance Publique Hôpitaux de Paris, Hôpital Necker Enfants Malades, Paris, France
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24
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Natsiavas P, Boyce RD, Jaulent MC, Koutkias V. OpenPVSignal: Advancing Information Search, Sharing and Reuse on Pharmacovigilance Signals via FAIR Principles and Semantic Web Technologies. Front Pharmacol 2018; 9:609. [PMID: 29997499 PMCID: PMC6028717 DOI: 10.3389/fphar.2018.00609] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Accepted: 05/21/2018] [Indexed: 12/27/2022] Open
Abstract
Signal detection and management is a key activity in pharmacovigilance (PV). When a new PV signal is identified, the respective information is publicly communicated in the form of periodic newsletters or reports by organizations that monitor and investigate PV-related information (such as the World Health Organization and national PV centers). However, this type of communication does not allow for systematic access, discovery and explicit data interlinking and, therefore, does not facilitate automated data sharing and reuse. In this paper, we present OpenPVSignal, a novel ontology aiming to support the semantic enrichment and rigorous communication of PV signal information in a systematic way, focusing on two key aspects: (a) publishing signal information according to the FAIR (Findable, Accessible, Interoperable, and Re-usable) data principles, and (b) exploiting automatic reasoning capabilities upon the interlinked PV signal report data. OpenPVSignal is developed as a reusable, extendable and machine-understandable model based on Semantic Web standards/recommendations. In particular, it can be used to model PV signal report data focusing on: (a) heterogeneous data interlinking, (b) semantic and syntactic interoperability, (c) provenance tracking and (d) knowledge expressiveness. OpenPVSignal is built upon widely-accepted semantic models, namely, the provenance ontology (PROV-O), the Micropublications semantic model, the Web Annotation Data Model (WADM), the Ontology of Adverse Events (OAE) and the Time ontology. To this end, we describe the design of OpenPVSignal and demonstrate its applicability as well as the reasoning capabilities enabled by its use. We also provide an evaluation of the model against the FAIR data principles. The applicability of OpenPVSignal is demonstrated by using PV signal information published in: (a) the World Health Organization's Pharmaceuticals Newsletter, (b) the Netherlands Pharmacovigilance Centre Lareb Web site and (c) the U.S. Food and Drug Administration (FDA) Drug Safety Communications, also available on the FDA Web site.
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Affiliation(s)
- Pantelis Natsiavas
- Centre for Research & Technology Hellas, Institute of Applied Biosciences, Thessaloniki, Greece.,Lab of Computing, Medical Informatics & Biomedical Imaging Technologies, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Richard D Boyce
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Marie-Christine Jaulent
- Institut National de la Santé et de la Recherche Médicale, U1142, LIMICS, Paris, France.,Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France.,Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, Villetaneuse, France
| | - Vassilis Koutkias
- Centre for Research & Technology Hellas, Institute of Applied Biosciences, Thessaloniki, Greece.,Lab of Computing, Medical Informatics & Biomedical Imaging Technologies, Department of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
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25
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Karapetiantz P, Bellet F, Audeh B, Lardon J, Leprovost D, Aboukhamis R, Morlane-Hondère F, Grouin C, Burgun A, Katsahian S, Jaulent MC, Beyens MN, Lillo-Le Louët A, Bousquet C. Descriptions of Adverse Drug Reactions Are Less Informative in Forums Than in the French Pharmacovigilance Database but Provide More Unexpected Reactions. Front Pharmacol 2018; 9:439. [PMID: 29765326 PMCID: PMC5938397 DOI: 10.3389/fphar.2018.00439] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 04/13/2018] [Indexed: 01/28/2023] Open
Abstract
Background: Social media have drawn attention for their potential use in Pharmacovigilance. Recent work showed that it is possible to extract information concerning adverse drug reactions (ADRs) from posts in social media. The main objective of the Vigi4MED project was to evaluate the relevance and quality of the information shared by patients on web forums about drug safety and its potential utility for pharmacovigilance. Methods: After selecting websites of interest, we manually evaluated the relevance of the content of posts for pharmacovigilance related to six drugs (agomelatine, baclofen, duloxetine, exenatide, strontium ranelate, and tetrazepam). We compared forums to the French Pharmacovigilance Database (FPVD) to (1) evaluate whether they contained relevant information to characterize a pharmacovigilance case report (patient’s age and sex; treatment indication, dose and duration; time-to-onset (TTO) and outcome of the ADR, and drug dechallenge and rechallenge) and (2) perform impact analysis (nature, seriousness, unexpectedness, and outcome of the ADR). Results: The cases in the FPVD were significantly more informative than posts in forums for patient description (age, sex), treatment description (dose, duration, TTO), and outcome of the ADR, but the indication for the treatment was more often found in forums. Cases were more often serious in the FPVD than in forums (46% vs. 4%), but forums more often contained an unexpected ADR than the FPVD (24% vs. 17%). Moreover, 197 unexpected ADRs identified in forums were absent from the FPVD and the distribution of the MedDRA System Organ Classes (SOCs) was different between the two data sources. Discussion: This study is the first to evaluate if patients’ posts may qualify as potential and informative case reports that should be stored in a pharmacovigilance database in the same way as case reports submitted by health professionals. The posts were less informative (except for the indication) and focused on less serious ADRs than the FPVD cases, but more unexpected ADRs were presented in forums than in the FPVD and their SOCs were different. Thus, web forums should be considered as a secondary, but complementary source for pharmacovigilance.
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Affiliation(s)
- Pierre Karapetiantz
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Florelle Bellet
- Centre Régional de Pharmacovigilance, Centre Hospitalier Universitaire de Saint-Étienne, Hôpital Nord, Saint-Étienne, France
| | - Bissan Audeh
- Université de Lyon, IMT Mines Saint-Etienne, Institut Henri Fayol, Département ISI, Université Jean Monnet, Institut d'Optique Graduate School, Centre National de la Recherche Scientifique, Laboratoire Hubert Curien, Saint-Étienne, France
| | - Jérémy Lardon
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Damien Leprovost
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Rim Aboukhamis
- Centre Régional de Pharmacovigilance, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | | | - Cyril Grouin
- LIMSI, CNRS, Université Paris-Saclay, Orsay, France
| | - Anita Burgun
- INSERM UMRS1138 Centre de Recherche des Cordeliers, Paris, France.,Département d'Informatique Médicale, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Sandrine Katsahian
- INSERM UMRS1138 Centre de Recherche des Cordeliers, Paris, France.,Département d'Informatique Médicale, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Marie-Christine Jaulent
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
| | - Marie-Noëlle Beyens
- Centre Régional de Pharmacovigilance, Centre Hospitalier Universitaire de Saint-Étienne, Hôpital Nord, Saint-Étienne, France
| | - Agnès Lillo-Le Louët
- Centre Régional de Pharmacovigilance, Hôpital Européen Georges-Pompidou, Assistance Publique - Hôpitaux de Paris, Paris, France
| | - Cédric Bousquet
- Sorbonne Université, INSERM, Université Paris 13, Laboratoire d'Informatique Médicale et d'Ingénierie des Connaissances en e-Santé, Paris, France
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26
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Farnia T, Jaulent MC, Steichen O. Evaluation Criteria of Noninvasive Telemonitoring for Patients With Heart Failure: Systematic Review. J Med Internet Res 2018; 20:e16. [PMID: 29339348 PMCID: PMC6257336 DOI: 10.2196/jmir.7873] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Revised: 10/18/2017] [Accepted: 11/20/2017] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Telemonitoring can improve heart failure (HF) management, but there is no standardized evaluation framework to comprehensively evaluate its impact. OBJECTIVE Our objectives were to list the criteria used in published evaluations of noninvasive HF telemonitoring projects, describe how they are used in the evaluation studies, and organize them into a consistent scheme. METHODS Articles published from January 1990 to August 2015 were obtained through MEDLINE, Web of Science, and EMBASE. Articles were eligible if they were original reports of a noninvasive HF telemonitoring evaluation study in the English language. Studies of implantable telemonitoring devices were excluded. Each selected article was screened to extract the description of the telemonitoring project and the evaluation process and criteria. A qualitative synthesis was performed. RESULTS We identified and reviewed 128 articles leading to 52 evaluation criteria classified into 6 dimensions: clinical, economic, user perspective, educational, organizational, and technical. The clinical and economic impacts were evaluated in more than 70% of studies, whereas the educational, organizational, and technical impacts were studied in fewer than 15%. User perspective was the most frequently covered dimension in the development phase of telemonitoring projects, whereas clinical and economic impacts were the focus of later phases. CONCLUSIONS Telemonitoring evaluation frameworks should cover all 6 dimensions appropriately distributed along the telemonitoring project lifecycle. Our next goal is to build such a comprehensive evaluation framework for telemonitoring and test it on an ongoing noninvasive HF telemonitoring project.
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Affiliation(s)
- Troskah Farnia
- Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en eSanté, Institut National de la Santé et de la Recherche Médicale, Sorbonne Universités, Université Paris 13, Sorbonne Paris Cité, Paris, France
| | - Marie-Christine Jaulent
- Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en eSanté, Institut National de la Santé et de la Recherche Médicale, Sorbonne Universités, Université Paris 13, Sorbonne Paris Cité, Paris, France
| | - Olivier Steichen
- Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en eSanté, Institut National de la Santé et de la Recherche Médicale, Sorbonne Universités, Université Paris 13, Sorbonne Paris Cité, Paris, France.,Department of Internal Medicine, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, Paris, France
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27
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Ugon A, Hadj Bouzid AI, Jaulent MC, Favre M, Duclos C, Jobez E, Falcoff H, Lamy JB, Tsopra R. Building a Knowledge-Based Tool for Auto-Assessing the Cardiovascular Risk. Stud Health Technol Inform 2018; 247:735-739. [PMID: 29678058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The prevention of cardiovascular diseases needs first to quantify the cardiovascular risk. To estimate this risk, French national health authorities provided clinical practice guidelines extending the existing European SCORE, which doesn't include all the cardiovascular risk factors (e.g. diabetes). Hence, French national clinical practice guidelines to quantify the cardiovascular risk is able to deal with more clinical situations than the SCORE. The goal of this paper is to formalize knowledge extracted from these guidelines and implement the rules so that they can be used into an auto-assessing tool of cardiovascular risk. Formalization followed five steps and was conducted under the guidance of medical experts. It resulted into a decision tree fed by eight decision variables. Evaluation of the accuracy of the decision tree showed 80% of agreement with an expert in medical informatics in predicting the cardiovascular risk level for 15 different clinical situations. Discrepancies correspond to the knowledge gaps within Clinical Practice Guidelines. We intend to extend the implementation of the decision tree to a complete tool, for allowing patient to auto-assess their cardiovascular risk. This tool will be integrated into a platform providing recommendations adapted to the calculated level of cardiovascular risk.
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Affiliation(s)
- Adrien Ugon
- ESIEE-Paris, Cité Descartes, 2 Boulevard Blaise Pascal, 93160 Noisy-le-Grand
| | - Amel Imene Hadj Bouzid
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
| | - Marie-Christine Jaulent
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
| | | | - Catherine Duclos
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
| | - Emmanuel Jobez
- Société de Formation Thérapeutique du Généraliste, France
| | - Hector Falcoff
- Société de Formation Thérapeutique du Généraliste, France
| | - Jean-Baptiste Lamy
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
| | - Rosy Tsopra
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
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Ugon A, Jobez E, Falcoff H, Jaulent MC, Meneton P, Favre M, Tsopra R. Modular Knowledge-Based Decision Support System Dedicated to a Cooperative Decision to Prevent Cardiovascular Diseases. Stud Health Technol Inform 2018; 255:200-204. [PMID: 30306936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Despite the success of artificial intelligence solutions in the recent years, physicians are still reticent to use integrated functionalities to support their decision. Methods used to create these functionalities can be divided into two groups, each being associated to different questions. Data-based methods are seen as black boxes for which it is impossible to understand how the decision is taken; knowledge-based methods need to rely on formalized knowledge sources on the basis of evidence, which can be discussed and criticized by physicians for their use in real life. This paper presents a new modular decision support system for the prevention of cardiovascular diseases, based on knowledge and on cooperative decision between the patient and the physician. The decision support system is based on two layers: (i) the first layer is a knowledge-based module which generates automatically patient profile, and prevention strategies associated to the profile; (ii) the second layer is a dynamic collaborative graphic user interface which displayed information about the risks of treatment adherence failure, personalized motivation and follow-up strategies. In the future, we aim at assessing the platform in real life.
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Affiliation(s)
| | - Emmanuel Jobez
- Société de Formation Thérapeutique du Généraliste, France
| | - Hector Falcoff
- Société de Formation Thérapeutique du Généraliste, France
| | - Marie-Christine Jaulent
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
| | - Pierre Meneton
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
| | | | - Rosy Tsopra
- LIMICS, INSERM UMRS 1142, Université Paris 13, Sorbonne Paris Cité, 93017 Bobigny, France UPMC Université Paris 6, Sorbonne Universités, Paris
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29
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Ugon A, Duclos C, Konate S, Arnedos Lopez S, Yazidi H, Venot A, Jaulent MC, Tsopra R. Parallel Design of Browsing Scheme and Data Model for Multi-Level Hierarchical Application Devoted to Management of Patient with Infectious Disease in Primary Care. Stud Health Technol Inform 2017; 235:421-425. [PMID: 28423827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Many decision systems are based on a hierarchical approach, enriching the known context used to finally choose the right potential action. Designing the scheme for browsing the clinical guidelines is a task devoted to expert in infectious diseases. Designing the data model is a task devoted to the expert in data modeling. As a consequence, browsing scheme and data model generally differ in terms of abstraction levels. While the browsing scheme proposes to navigate into depth, the data model stays flat. We propose here a novel method to design in parallel the browsing scheme and the data model so that both of them reflect the different abstraction levels in decision process.
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Affiliation(s)
- Adrien Ugon
- Sorbonne Universités, UPMC Univ Paris 06, UMR 7606, LIP6, Paris, France
| | - Catherine Duclos
- Sorbonne Universités, UPMC Univ Paris 06, INSERM Sorbonne Paris Cité, Université Paris 13, LIMICS, UMR_S 1142, Paris, France
| | - Salamata Konate
- Sorbonne Universités, UPMC Univ Paris 06, INSERM Sorbonne Paris Cité, Université Paris 13, LIMICS, UMR_S 1142, Paris, France
| | - Sarah Arnedos Lopez
- Sorbonne Universités, UPMC Univ Paris 06, INSERM Sorbonne Paris Cité, Université Paris 13, LIMICS, UMR_S 1142, Paris, France
| | - Hechem Yazidi
- Sorbonne Universités, UPMC Univ Paris 06, INSERM Sorbonne Paris Cité, Université Paris 13, LIMICS, UMR_S 1142, Paris, France
| | - Alain Venot
- Sorbonne Universités, UPMC Univ Paris 06, INSERM Sorbonne Paris Cité, Université Paris 13, LIMICS, UMR_S 1142, Paris, France
| | - Marie-Christine Jaulent
- Sorbonne Universités, UPMC Univ Paris 06, INSERM Sorbonne Paris Cité, Université Paris 13, LIMICS, UMR_S 1142, Paris, France
| | - Rosy Tsopra
- Sorbonne Universités, UPMC Univ Paris 06, INSERM Sorbonne Paris Cité, Université Paris 13, LIMICS, UMR_S 1142, Paris, France
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Richard M, Aimé X, Jaulent MC, Krebs MO, Charlet J. From Patient Discharge Summaries to an Ontology for Psychiatry. Stud Health Technol Inform 2017; 245:930-934. [PMID: 29295236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Psychiatry aims at detecting symptoms, providing diagnoses and treating mental disorders. We developed ONTOPSYCHIA, an ontology for psychiatry in three modules: social and environmental factors of mental disorders, mental disorders, and treatments. The use of ONTOPSYCHIA, associated with dedicated tools, will facilitate semantic research in Patient Discharge Summaries (PDS). To develop the first module of the ontology we propose a PDS text analysis in order to explicit psychiatry concepts. We decided to set aside classifications during the construction of the modu le, to focus only on the information contained in PDS (bottom-up approach) and to return to domain classifications solely for the enrichment phase (top-down approach). Then, we focused our work on the development of the LOVMI methodology (Les Ontologies Validées par Méthode Interactive - Ontologies Validated by Interactive Method), which aims to provide a methodological framework to validate the structure and the semantic of an ontology.
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Affiliation(s)
- Marion Richard
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Xavier Aimé
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Marie-Odile Krebs
- Laboratoire de Pathophysiologie des Troubles Psychiatriques, Centre Hosp. Sainte-Anne, Paris, France
| | - Jean Charlet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
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Tsopra R, Kinouani S, Venot A, Jaulent MC, Duclos C, Lamy JB. Design of a Visual Interface for Comparing Antibiotics Using Rainbow Boxes. Stud Health Technol Inform 2017; 235:529-533. [PMID: 28423849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Non-optimal prescriptions of antibiotics have a negative impact on patients and population. Clinical practice guidelines are not always followed by doctors because the rationale of the recommendations is not always clear and can be difficult to understand. In this paper, we propose a new approach consisting in presenting the properties of antibiotics for allowing doctors to compare them and choose the most appropriate one. For that, we used and extended rainbow boxes, a new technique for overlapping set visualization. We tested our approach on 11 clinical situations related to urinary infections, and assessed the simplicity, the interest and utility with 11 doctors. 10 of them found that this approach was interesting and useful in clinical practice. Further studies are needed to confirm this preliminary work.
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Affiliation(s)
- Rosy Tsopra
- LIMICS, INSERM UMRS 1142, Université Paris 13, UPMC Université Paris 6, Paris, France
| | | | - Alain Venot
- LIMICS, INSERM UMRS 1142, Université Paris 13, UPMC Université Paris 6, Paris, France
| | | | - Catherine Duclos
- LIMICS, INSERM UMRS 1142, Université Paris 13, UPMC Université Paris 6, Paris, France
| | - Jean-Baptiste Lamy
- LIMICS, INSERM UMRS 1142, Université Paris 13, UPMC Université Paris 6, Paris, France
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Koutkias VG, Lillo-Le Louët A, Jaulent MC. Exploiting heterogeneous publicly available data sources for drug safety surveillance: computational framework and case studies. Expert Opin Drug Saf 2016; 16:113-124. [PMID: 27813420 DOI: 10.1080/14740338.2017.1257604] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Driven by the need of pharmacovigilance centres and companies to routinely collect and review all available data about adverse drug reactions (ADRs) and adverse events of interest, we introduce and validate a computational framework exploiting dominant as well as emerging publicly available data sources for drug safety surveillance. METHODS Our approach relies on appropriate query formulation for data acquisition and subsequent filtering, transformation and joint visualization of the obtained data. We acquired data from the FDA Adverse Event Reporting System (FAERS), PubMed and Twitter. In order to assess the validity and the robustness of the approach, we elaborated on two important case studies, namely, clozapine-induced cardiomyopathy/myocarditis versus haloperidol-induced cardiomyopathy/myocarditis, and apixaban-induced cerebral hemorrhage. RESULTS The analysis of the obtained data provided interesting insights (identification of potential patient and health-care professional experiences regarding ADRs in Twitter, information/arguments against an ADR existence across all sources), while illustrating the benefits (complementing data from multiple sources to strengthen/confirm evidence) and the underlying challenges (selecting search terms, data presentation) of exploiting heterogeneous information sources, thereby advocating the need for the proposed framework. CONCLUSIONS This work contributes in establishing a continuous learning system for drug safety surveillance by exploiting heterogeneous publicly available data sources via appropriate support tools.
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Affiliation(s)
- Vassilis G Koutkias
- a Institute of Applied Biosciences , Centre for Research & Technology Hellas , Thermi , Thessaloniki , Greece.,b INSERM, U1142, LIMICS , F-75006 , Paris , France.,c Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS 1142, LIMICS, F-75006 , Paris , France.,d Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142) , F-93430 , Villetaneuse , France
| | - Agnès Lillo-Le Louët
- e Centre Reìgional de Pharmacovigilance, Hôpital Européen Georges-Pompidou, AP-HP , F-75015 , Paris , France
| | - Marie-Christine Jaulent
- b INSERM, U1142, LIMICS , F-75006 , Paris , France.,c Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS 1142, LIMICS, F-75006 , Paris , France.,d Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142) , F-93430 , Villetaneuse , France
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Asfari H, Souvignet J, Lillo-Le Louët A, Trombert B, Jaulent MC, Bousquet C. [Automated grouping of terms associated to cardiac valve fibrosis in MedDRA]. Therapie 2016; 71:541-552. [PMID: 27692980 DOI: 10.1016/j.therap.2016.06.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2016] [Accepted: 06/24/2016] [Indexed: 10/21/2022]
Abstract
AIM To propose an alternative approach for building custom groupings of terms that complements the usual approach based on both hierarchical method (selection of reference groupings in medical dictionary for regulatory activities [MedDRA]) and/or textual method (string search), for case reports extraction from a pharmacovigilance database in response to a safety problem. Here we take cardiac valve fibrosis as an example. METHODS The list of terms obtained by an automated approach, based on querying ontology of adverse drug reactions (OntoADR), a knowledge base defining MedDRA terms through relationships with systematized nomenclature of medicine-clinical terms (SNOMED CT) concepts, was compared with the reference list consisting of 53 preferred terms obtained by hierarchical and textual method. Two queries were performed on OntoADR by using a dedicated software: OntoADR query tools. Both queries excluded congenital diseases, and included a procedure or an auscultation method performed on cardiac valve structures. Query 1 also considered MedDRA terms related to fibrosis, narrowing or calcification of heart valves, and query 2 MedDRA terms described according to one of these four SNOMED CT terms: "Insufficiency", "Valvular sclerosis", "Heart valve calcification" or "Heart valve stenosis". RESULTS The reference grouping consisted of 53 MedDRA preferred terms. Our automated method achieved recall of 79% and precision of 100% for query 1 privileging morphological abnormalities, and recall of 100% and precision of 96% for query 2 privileging functional abnormalities. CONCLUSION An alternative approach to MedDRA reference groupings for building custom groupings is feasible for cardiac valve fibrosis. OntoADR is still in development. Its application to other adverse reactions would require significant work for a knowledge engineer to define every MedDRA term, but such definitions could then be queried as many times as necessary by pharmacovigilance professionals.
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Affiliation(s)
- Hadyl Asfari
- UMR_S 1142, Inserm, LIMICS, Sorbonne universités, UPMC université Paris 06, 75006 Paris, France; Service de santé publique et d'information médicale, hôpital nord, centre hospitalier universitaire de Saint-Etienne, 42270 Saint-Etienne, France.
| | - Julien Souvignet
- UMR_S 1142, Inserm, LIMICS, Sorbonne universités, UPMC université Paris 06, 75006 Paris, France; Service de santé publique et d'information médicale, hôpital nord, centre hospitalier universitaire de Saint-Etienne, 42270 Saint-Etienne, France
| | - Agnès Lillo-Le Louët
- Centre régional de pharmacovigilance, hôpital européen Georges-Pompidou, AP-HP, 75015 Paris, France
| | - Béatrice Trombert
- Service de santé publique et d'information médicale, hôpital nord, centre hospitalier universitaire de Saint-Etienne, 42270 Saint-Etienne, France
| | - Marie-Christine Jaulent
- UMR_S 1142, Inserm, LIMICS, Sorbonne universités, UPMC université Paris 06, 75006 Paris, France
| | - Cédric Bousquet
- UMR_S 1142, Inserm, LIMICS, Sorbonne universités, UPMC université Paris 06, 75006 Paris, France; Service de santé publique et d'information médicale, hôpital nord, centre hospitalier universitaire de Saint-Etienne, 42270 Saint-Etienne, France
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Daniel C, Ouagne D, Sadou E, Forsberg K, Gilchrist MM, Zapletal E, Paris N, Hussain S, Jaulent MC, Kalra D. Cross border semantic interoperability for clinical research: the EHR4CR semantic resources and services. AMIA Jt Summits Transl Sci Proc 2016; 2016:51-9. [PMID: 27570649 PMCID: PMC5001763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/31/2022]
Abstract
With the development of platforms enabling the use of routinely collected clinical data in the context of international clinical research, scalable solutions for cross border semantic interoperability need to be developed. Within the context of the IMI EHR4CR project, we first defined the requirements and evaluation criteria of the EHR4CR semantic interoperability platform and then developed the semantic resources and supportive services and tooling to assist hospital sites in standardizing their data for allowing the execution of the project use cases. The experience gained from the evaluation of the EHR4CR platform accessing to semantically equivalent data elements across 11 European participating EHR systems from 5 countries demonstrated how far the mediation model and mapping efforts met the expected requirements of the project. Developers of semantic interoperability platforms are beginning to address a core set of requirements in order to reach the goal of developing cross border semantic integration of data.
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Affiliation(s)
- Christel Daniel
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France;; AP-HP, Paris, France
| | - David Ouagne
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France
| | - Eric Sadou
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France;; AP-HP, Paris, France
| | | | | | | | | | - Sajjad Hussain
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France
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Souvignet J, Declerck G, Asfari H, Jaulent MC, Bousquet C. OntoADR a semantic resource describing adverse drug reactions to support searching, coding, and information retrieval. J Biomed Inform 2016; 63:100-107. [PMID: 27369567 DOI: 10.1016/j.jbi.2016.06.010] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Revised: 06/25/2016] [Accepted: 06/27/2016] [Indexed: 10/21/2022]
Abstract
INTRODUCTION Efficient searching and coding in databases that use terminological resources requires that they support efficient data retrieval. The Medical Dictionary for Regulatory Activities (MedDRA) is a reference terminology for several countries and organizations to code adverse drug reactions (ADRs) for pharmacovigilance. Ontologies that are available in the medical domain provide several advantages such as reasoning to improve data retrieval. The field of pharmacovigilance does not yet benefit from a fully operational ontology to formally represent the MedDRA terms. Our objective was to build a semantic resource based on formal description logic to improve MedDRA term retrieval and aid the generation of on-demand custom groupings by appropriately and efficiently selecting terms: OntoADR. METHODS The method consists of the following steps: (1) mapping between MedDRA terms and SNOMED-CT, (2) generation of semantic definitions using semi-automatic methods, (3) storage of the resource and (4) manual curation by pharmacovigilance experts. RESULTS We built a semantic resource for ADRs enabling a new type of semantics-based term search. OntoADR adds new search capabilities relative to previous approaches, overcoming the usual limitations of computation using lightweight description logic, such as the intractability of unions or negation queries, bringing it closer to user needs. Our automated approach for defining MedDRA terms enabled the association of at least one defining relationship with 67% of preferred terms. The curation work performed on our sample showed an error level of 14% for this automated approach. We tested OntoADR in practice, which allowed us to build custom groupings for several medical topics of interest. DISCUSSION The methods we describe in this article could be adapted and extended to other terminologies which do not benefit from a formal semantic representation, thus enabling better data retrieval performance. Our custom groupings of MedDRA terms were used while performing signal detection, which suggests that the graphical user interface we are currently implementing to process OntoADR could be usefully integrated into specialized pharmacovigilance software that rely on MedDRA.
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Affiliation(s)
- Julien Souvignet
- INSERM, U1142, LIMICS, F-75006 Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006 Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430 Villetaneuse, France; SSPIM, CHU University Hospital of Saint Etienne, Saint Etienne, France
| | - Gunnar Declerck
- Sorbonne Universités, Université de technologie de Compiègne, EA 2223 Costech (Connaissance, Organisation et Systèmes Techniques), Centre Pierre Guillaumat, CS 60 319, 60 203 Compiègne cedex, France
| | - Hadyl Asfari
- INSERM, U1142, LIMICS, F-75006 Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006 Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430 Villetaneuse, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006 Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006 Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430 Villetaneuse, France
| | - Cédric Bousquet
- INSERM, U1142, LIMICS, F-75006 Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006 Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430 Villetaneuse, France; SSPIM, CHU University Hospital of Saint Etienne, Saint Etienne, France.
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Koutkias V, Jaulent MC. A Multiagent System for Integrated Detection of Pharmacovigilance Signals. J Med Syst 2015; 40:37. [DOI: 10.1007/s10916-015-0378-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2015] [Accepted: 10/09/2015] [Indexed: 12/23/2022]
Affiliation(s)
- Vassilis Koutkias
- INSERM, U1142, LIMICS, 75006, Paris, France. .,Sorbonne Universités, UPMC University Paris 06, UMR_S 1142, LIMICS, 75006, Paris, France. .,Université Paris 13, Sorbonne Paris Cité, LIMICS, UMR_S 1142, 93430, Villetaneuse, France.
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, 75006, Paris, France. .,Sorbonne Universités, UPMC University Paris 06, UMR_S 1142, LIMICS, 75006, Paris, France. .,Université Paris 13, Sorbonne Paris Cité, LIMICS, UMR_S 1142, 93430, Villetaneuse, France.
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Maaroufi M, Choquet R, Landais P, Jaulent MC. Towards data integration automation for the French rare disease registry. AMIA Annu Symp Proc 2015; 2015:880-885. [PMID: 26958224 PMCID: PMC4765585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Building a medical registry upon an existing infrastructure and rooted practices is not an easy task. It is the case for the BNDMR project, the French rare disease registry, that aims to collect administrative and medical data of rare disease patients seen in different hospitals. To avoid duplicating data entry for health professionals, the project plans to deploy connectors with the existing systems to automatically retrieve data. Given the data heterogeneity and the large number of source systems, the automation of connectors creation is required. In this context, we propose a methodology that optimizes the use of existing alignment approaches in the data integration processes. The generated mappings are formalized in exploitable mapping expressions. Following this methodology, a process has been experimented on specific data types of a source system: Boolean and predefined lists. As a result, effectiveness of the used alignment approach has been enhanced and more good mappings have been detected. Nonetheless, further improvements could be done to deal with the semantic issue and process other data types.
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Affiliation(s)
- Meriem Maaroufi
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France; INSERM, U1142, LIMICS, Paris, France
| | - Rémy Choquet
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France; INSERM, U1142, LIMICS, Paris, France
| | - Paul Landais
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France; Montpellier University, EA2415 & BESPIM, University Hospital Nîmes, France
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Lardon J, Abdellaoui R, Bellet F, Asfari H, Souvignet J, Texier N, Jaulent MC, Beyens MN, Burgun A, Bousquet C. Adverse Drug Reaction Identification and Extraction in Social Media: A Scoping Review. J Med Internet Res 2015; 17:e171. [PMID: 26163365 PMCID: PMC4526988 DOI: 10.2196/jmir.4304] [Citation(s) in RCA: 79] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2015] [Revised: 04/09/2015] [Accepted: 04/22/2015] [Indexed: 02/06/2023] Open
Abstract
Background The underreporting of adverse drug reactions (ADRs) through traditional reporting channels is a limitation in the efficiency of the current pharmacovigilance system. Patients’ experiences with drugs that they report on social media represent a new source of data that may have some value in postmarketing safety surveillance. Objective A scoping review was undertaken to explore the breadth of evidence about the use of social media as a new source of knowledge for pharmacovigilance. Methods Daubt et al’s recommendations for scoping reviews were followed. The research questions were as follows: How can social media be used as a data source for postmarketing drug surveillance? What are the available methods for extracting data? What are the different ways to use these data? We queried PubMed, Embase, and Google Scholar to extract relevant articles that were published before June 2014 and with no lower date limit. Two pairs of reviewers independently screened the selected studies and proposed two themes of review: manual ADR identification (theme 1) and automated ADR extraction from social media (theme 2). Descriptive characteristics were collected from the publications to create a database for themes 1 and 2. Results Of the 1032 citations from PubMed and Embase, 11 were relevant to the research question. An additional 13 citations were added after further research on the Internet and in reference lists. Themes 1 and 2 explored 11 and 13 articles, respectively. Ways of approaching the use of social media as a pharmacovigilance data source were identified. Conclusions This scoping review noted multiple methods for identifying target data, extracting them, and evaluating the quality of medical information from social media. It also showed some remaining gaps in the field. Studies related to the identification theme usually failed to accurately assess the completeness, quality, and reliability of the data that were analyzed from social media. Regarding extraction, no study proposed a generic approach to easily adding a new site or data source. Additional studies are required to precisely determine the role of social media in the pharmacovigilance system.
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Affiliation(s)
- Jérémy Lardon
- Université Paris 13, Sorbonne Paris Cité, Laboratoire d'Informatique Médicale et d'Ingénieurie des Connaissances en e-Santé (LIMICS), (Unité Mixte de Recherche en Santé, UMR_S 1142), F-93430, Villetaneuse, France, Sorbonne Universités, University of Pierre and Marie Curie (UPMC) Université Paris 06, Unité Mixte de Recherche en Santé (UMR_S) 1142, Laboratoire d'Informatique Médicale et d'Ingénieurie des Connaissances en e-Santé (LIMICS), F-75006, Institut National de la Santé et de la Recherche Médicale (INSERM), U1142, Laboratoire d'Informatique Médicale et d'Ingénieurie des Connaissances en e-Santé (LIMICS), F-75006, Paris, France.
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Abstract
Computational signal detection constitutes a key element of postmarketing drug monitoring and surveillance. Diverse data sources are considered within the 'search space' of pharmacovigilance scientists, and respective data analysis methods are employed, all with their qualities and shortcomings, towards more timely and accurate signal detection. Recent systematic comparative studies highlighted not only event-based and data-source-based differential performance across methods but also their complementarity. These findings reinforce the arguments for exploiting all possible information sources for drug safety and the parallel use of multiple signal detection methods. Combinatorial signal detection has been pursued in few studies up to now, employing a rather limited number of methods and data sources but illustrating well-promising outcomes. However, the large-scale realization of this approach requires systematic frameworks to address the challenges of the concurrent analysis setting. In this paper, we argue that semantic technologies provide the means to address some of these challenges, and we particularly highlight their contribution in (a) annotating data sources and analysis methods with quality attributes to facilitate their selection given the analysis scope; (b) consistently defining study parameters such as health outcomes and drugs of interest, and providing guidance for study setup; (c) expressing analysis outcomes in a common format enabling data sharing and systematic comparisons; and (d) assessing/supporting the novelty of the aggregated outcomes through access to reference knowledge sources related to drug safety. A semantically-enriched framework can facilitate seamless access and use of different data sources and computational methods in an integrated fashion, bringing a new perspective for large-scale, knowledge-intensive signal detection.
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Affiliation(s)
- Vassilis G Koutkias
- INSERM, U1142, LIMICS, Campus des Cordeliers, 15 rue de l' École de Médecine, 75006, Paris, France,
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Toubiana L, Ugon A, Giavarini A, Riquier J, Charlet J, Jeunemaitre X, Plouin PF, Jaulent MC. A "pivot" Model to set up Large Scale Rare Diseases Information Systems: Application to the Fibromuscular Dysplasia Registry. Stud Health Technol Inform 2015; 210:887-891. [PMID: 25991283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
The SIR-FMD project is a partnership between the Department of Genetics and Reference Centre for Rare Vascular Diseases at the Georges Pompidou European Hospital in Paris and the Medical Informatics and Knowledge Engineering Laboratory of Inserm. Its aim is to use an ontological approach to implement an information system for the French Fibromuscular Dysplasia Registry. The existing data was dispersed in numerous databases, which had been created independently. These databases have different structures and contain data of diverse quality. The project aims to provide generic solutions for the management of the communication of medical data. The secondary objective is to demonstrate the applicability of these generic solutions in the field of rare diseases (RD) in an operational context. The construction of the French FMD registry was a multistep process. A secure platform has been available since the beginning of November 2013. The medical records of 471 patients from the initial dataset provided by the HEGP-Paris, France have been included, and are accessible from a secure user account. Users are organized into a collaborative group, and can access patient groups. Each electronic patient record contains more than 2,200 items. The problem of semantic interoperability has become one of the major challenges for the development of applications requiring the sharing and reuse of data. The information system component of the SIR-FMD project has a direct impact on the standardisation of coding of rare diseases and thereby contributes to the development of e-Health.
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Affiliation(s)
- Laurent Toubiana
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, F-93430, Villetaneuse, France
| | - Adrien Ugon
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, F-93430, Villetaneuse, France
| | - Alessandra Giavarini
- Hypertension unit, department of genetics and rare vascular diseases reference center; Hopital Europeen G Pompidou (HEGP); Paris-Descartes University
| | - Jérémie Riquier
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, F-93430, Villetaneuse, France
| | - Jean Charlet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, F-93430, Villetaneuse, France
| | - Xavier Jeunemaitre
- Hypertension unit, department of genetics and rare vascular diseases reference center; Hopital Europeen G Pompidou (HEGP); Paris-Descartes University
| | - Pierre-François Plouin
- Hypertension unit, department of genetics and rare vascular diseases reference center; Hopital Europeen G Pompidou (HEGP); Paris-Descartes University
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, F-93430, Villetaneuse, France
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Jaulent MC, Assélé-Kama A, Savard S, Giavarini A, Touzé E, Jeunemaître X, Ugon A, Plouin PF, Toubiana L. Building a Semantic Interoperability Framework for Care and Research in Fibromuscular Dysplasia. Stud Health Technol Inform 2015; 216:217-221. [PMID: 26262042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
UNLABELLED Identifying patients with Fibromuscular Dysplasia (FMD) at the international level will have considerable value for understanding the epidemiology, clinical manifestations and susceptible genes in this arterial disease, but also for identifying eligible patients in clinical trials or cohorts. We present a two-step methodology to create a general semantic interoperability framework allowing access and comparison of distributed data over various nations, languages, formats and databases. METHODS The first step is to develop a pivot multidimensional model based on a core dataset to harmonize existing heterogeneous data sources. The second step is to align the model to additional data, semantically related to FMD and collected currently in various registries. We present the results of the first step that has been fully completed with the validation and implementation of the model in a dedicated information system (SIR-FMD). We discuss the current achievements for step 2 and the extensibility of the methodology in the context of other rare diseases.
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Affiliation(s)
- Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France
| | - Ariane Assélé-Kama
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France
| | - Sébastien Savard
- Hypertension unit, Department of genetics and Centre for rare vascular diseases; Hopital Europeen G Pompidou (HEGP); Paris-Descartes University ; INSERM U970, Paris Cardiovascular Research Centre, 75015 Paris, France
| | - Alessandra Giavarini
- Hypertension unit, Department of genetics and Centre for rare vascular diseases; Hopital Europeen G Pompidou (HEGP); Paris-Descartes University ; INSERM U970, Paris Cardiovascular Research Centre, 75015 Paris, France
| | - Emmanuel Touzé
- Université Caen Basse Normandie, CHU Côte-de-Nacre, service de neurologie et unité neurovasculaire, 14000 Caen, France; INSERM U919, GIP CYCERON, 14074 Caen, France
| | - Xavier Jeunemaître
- Hypertension unit, Department of genetics and Centre for rare vascular diseases; Hopital Europeen G Pompidou (HEGP); Paris-Descartes University ; INSERM U970, Paris Cardiovascular Research Centre, 75015 Paris, France
| | - Adrien Ugon
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France
| | - Pierre-François Plouin
- Hypertension unit, Department of genetics and Centre for rare vascular diseases; Hopital Europeen G Pompidou (HEGP); Paris-Descartes University ; INSERM U970, Paris Cardiovascular Research Centre, 75015 Paris, France
| | - Laurent Toubiana
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Université Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, F-93430, Villetaneuse, France
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Douali N, De Roo J, Sweetman P, Papageorgiou EI, Dollon J, Jaulent MC. Personalized decision support system based on clinical practice guidelines. Stud Health Technol Inform 2015; 211:308-310. [PMID: 25980889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Personalized medicine is a broad and rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. Health care that embraces personalized medicine is an integrated, coordinated, evidence based approach to individualizing patient care across the continuum. It is very important to make the right treatment decision but before that to obtain a good diagnosis. There are several clinical forms of disease whose symptoms vary depending on the age and etiology. In this study, we investigated and evaluated a model framework, for personalized diagnostic decisions, based on Case Based Fuzzy Cognitive Map (CBFCM, a cognitive process applying the main features of fuzzy logic and neural processors to situations involving imprecision and uncertain descriptions, in a similar way to intuitive human reasoning. We explored the use of this method for modelling clinical practice guidelines.
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Affiliation(s)
- Nassim Douali
- INSERM UMRS 1142, Medicine Faculty, Pierre and Marie Curie University, Sorbonne Universities, Paris, France
| | - Jos De Roo
- Agfa HealthCare, Agfa HealthCare NV, Gent, Belgium
| | | | - Elpiniki I Papageorgiou
- Department of Informatics & Computer Technology, Technological Educational Institute of Lamia, Greece
| | | | - Marie-Christine Jaulent
- INSERM UMRS 1142, Medicine Faculty, Pierre and Marie Curie University, Sorbonne Universities, Paris, France
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Lamas E, Barh A, Brown D, Jaulent MC. Ethical, Legal and Social Issues related to the health data-warehouses: re-using health data in the research and public health research. Stud Health Technol Inform 2015; 210:719-723. [PMID: 25991247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Research derived from the application of information and communication technologies in medicine operates in a context involving the globalization of collecting, sharing, storage, transfer and re-use of personal health data. Health data computerization within Clinical Information Systems (as Electronic Healthcare Records) should allow the re-use of health data for clinical research and public health purposes. One of the objects allowing the integration of healthcare and research information systems is the health data-warehouse (DWH). However, ethical-legal frameworks in force are not adapted to these DWHs because they were not conceived for re-using data in a different context than the one of their acquisition. For that matter, access modalities to data-warehouses must ensure the respect of patients' rights: information to the patient, as well as confidentiality and security. Through a bibliography research, some Ethical, legal and Social Issues (ELSI) have been identified: Patients' rights Modalities of implementation of the DWs; Solidarity and common good; Transparency and Trust. Comparative analysis between the Directive 95/46/CE and the "Proposal for regulation on protection of individuals with regard to the processing of personal data" shows that this regulation pretends allowing the re-use of key-coded data when aimed at a scientific purpose. However, since this new regulation does not align with the ethical and legal requirements at an operational level, a Code of practice on secondary use of Medical Data in scientific Research Projects has been developed at the European Level. This Code provides guidance for Innovative Medicine Initiative (IMI) and will help to propose practical solutions to overcome the issue of the re-use of data for research purposes.
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Affiliation(s)
- Eugenia Lamas
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Anne Barh
- R&D Compliance department SANOFI1, avenue Pierre Brossolette, 91385 CHILLY-MAZARIN, France
| | - Dario Brown
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
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Bousquet C, Sadou É, Souvignet J, Jaulent MC, Declerck G. Formalizing MedDRA to support semantic reasoning on adverse drug reaction terms. J Biomed Inform 2014; 49:282-91. [PMID: 24680984 DOI: 10.1016/j.jbi.2014.03.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2013] [Revised: 03/10/2014] [Accepted: 03/16/2014] [Indexed: 11/27/2022]
Abstract
Although MedDRA has obvious advantages over previous terminologies for coding adverse drug reactions and discovering potential signals using data mining techniques, its terminological organization constrains users to search terms according to predefined categories. Adding formal definitions to MedDRA would allow retrieval of terms according to a case definition that may correspond to novel categories that are not currently available in the terminology. To achieve semantic reasoning with MedDRA, we have associated formal definitions to MedDRA terms in an OWL file named OntoADR that is the result of our first step for providing an "ontologized" version of MedDRA. MedDRA five-levels original hierarchy was converted into a subsumption tree and formal definitions of MedDRA terms were designed using several methods: mappings to SNOMED-CT, semi-automatic definition algorithms or a fully manual way. This article presents the main steps of OntoADR conception process, its structure and content, and discusses problems and limits raised by this attempt to "ontologize" MedDRA.
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Affiliation(s)
- Cédric Bousquet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France; University of Saint Etienne, Department of Public Health and Medical Informatics, Saint-Etienne, France
| | - Éric Sadou
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Julien Souvignet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France; University of Saint Etienne, Department of Public Health and Medical Informatics, Saint-Etienne, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Gunnar Declerck
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France.
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Declerck G, Souvignet J, Rodrigues JM, Jaulent MC. Automatic annotation of ICD-to-MedDRA mappings with SKOS predicates. Stud Health Technol Inform 2014; 205:1013-1017. [PMID: 25160341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Robust alignments between ICD and MedDRA are essential to enable the secondary use of clinical data for pharmacovigilance research. UMLS makes available ICD-to-MedDRA mappings, but they are only poorly specified, which introduces difficulties when exploited in an automatic way. SKOS vocabulary can help achieve quality and machine-processable mappings. We have developed an algorithm based on several simple rules which annotates automatically ICD-to-MedDRA mappings with SKOS predicates. The method was tested and evaluated on a sample of ICD-10-to MedDRA mappings extracted from UMLS. The algorithm demonstrated satisfying performances, especially for skos:exactMatch properties, which suggests that automatic methods can be used to improve the quality of terminology mappings.
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Affiliation(s)
- Gunnar Declerck
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Julien Souvignet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Jean-Marie Rodrigues
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
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Parès Y, Aimé X, Charlet J, Jaulent MC. Towards an automatic harmonization of the representation of medical reports to assess their similarities. Stud Health Technol Inform 2014; 205:858-862. [PMID: 25160309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Numerous hospitals contain unexploited knowledge deposits. These often take the form of unstructured records with heterogeneous content, which, at various levels of those organizations, register past cases. Those records are for instance patient medical records. Accessing the knowledge and experience they gather would help us to handle present cases. We present here a method to normalize textual reports in foetopathology in order to constitute a proper case base that will be the target of case-based reasoning techniques. Statistics of noise and silence generated by this method on 10 cases are presented.
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Affiliation(s)
- Yves Parès
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS
| | - Xavier Aimé
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS
| | - Jean Charlet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS
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Souvignet J, Asfari H, Declerck G, Lardon J, Trombert-Paviot B, Jaulent MC, Bousquet C. Ci4SeR--curation interface for semantic resources--evaluation with adverse drug reactions. Stud Health Technol Inform 2014; 205:116-120. [PMID: 25160157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Evaluation and validation have become a crucial problem for the development of semantic resources. We developed Ci4SeR, a Graphical User Interface to optimize the curation work (not taking into account structural aspects), suitable for any type of resource with lightweight description logic. We tested it on OntoADR, an ontology of adverse drug reactions. A single curator has reviewed 326 terms (1020 axioms) in an estimated time of 120 hours (2.71 concepts and 8.5 axioms reviewed per hour) and added 1874 new axioms (15.6 axioms per hour). Compared with previous manual endeavours, the interface allows increasing the speed-rate of reviewed concepts by 68% and axiom addition by 486%. A wider use of Ci4SeR would help semantic resources curation and improve completeness of knowledge modelling.
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Affiliation(s)
- Julien Souvignet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Hadyl Asfari
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Gunnar Declerck
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Jérémy Lardon
- SSPIM, CHU University Hospital of Saint Etienne, France
| | - Béatrice Trombert-Paviot
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
| | - Cédric Bousquet
- INSERM, U1142, LIMICS, F-75006, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, F-75006, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), F-93430, Villetaneuse, France
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Maaroufi M, Choquet R, Landais P, Jaulent MC. Formalizing mappings to optimize automated schema alignment: application to rare diseases. Stud Health Technol Inform 2014; 205:283-287. [PMID: 25160191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
In the era of data sharing and systems interoperability, the automation of data schema alignment has become a priority. Discovering data mappings is the aim of many alignment approaches that have been described in the literature and the effectiveness of which depends on data specifications. In this context, we propose a method for mappings formalization that allows automated data integration processes optimization. This method, involving both data element level and value element level, allows an automated inference of mappings expressed by rules. In this paper, we start by describing the methods used to achieve this mappings formalization. Then, we explain how it has been validated by characterizing data from two use cases. We end up by discussing the objectives of the proposed formalization.
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Affiliation(s)
- Meriem Maaroufi
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Rémy Choquet
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Paul Landais
- Banque Nationale de Données Maladies Rares, Hôpital Necker Enfants Malades, Assistance Publique des Hôpitaux de Paris, Paris, France
| | - Marie-Christine Jaulent
- INSERM, U1142, LIMICS, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France; Université Paris 13, Sorbonne Paris Cité, UMR_S 1142, LIMICS, Villetaneuse, France
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Douali N, Abdennour M, Zucker JD, Jaulent MC. Formalization of Clinical Practice Guidelines: Nonalcoholic Steatohepatitis Diagnosis Model-Related Personalized Medicine. ACTA ACUST UNITED AC 2014. [DOI: 10.24105/ejbi.2014.10.1.3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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50
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Papageorgiou EI, Huszka C, De Roo J, Douali N, Jaulent MC, Colaert D. Application of probabilistic and fuzzy cognitive approaches in semantic web framework for medical decision support. Comput Methods Programs Biomed 2013; 112:580-598. [PMID: 23953959 DOI: 10.1016/j.cmpb.2013.07.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2012] [Revised: 07/15/2013] [Accepted: 07/17/2013] [Indexed: 06/02/2023]
Abstract
This study aimed to focus on medical knowledge representation and reasoning using the probabilistic and fuzzy influence processes, implemented in the semantic web, for decision support tasks. Bayesian belief networks (BBNs) and fuzzy cognitive maps (FCMs), as dynamic influence graphs, were applied to handle the task of medical knowledge formalization for decision support. In order to perform reasoning on these knowledge models, a general purpose reasoning engine, EYE, with the necessary plug-ins was developed in the semantic web. The two formal approaches constitute the proposed decision support system (DSS) aiming to recognize the appropriate guidelines of a medical problem, and to propose easily understandable course of actions to guide the practitioners. The urinary tract infection (UTI) problem was selected as the proof-of-concept example to examine the proposed formalization techniques implemented in the semantic web. The medical guidelines for UTI treatment were formalized into BBN and FCM knowledge models. To assess the formal models' performance, 55 patient cases were extracted from a database and analyzed. The results showed that the suggested approaches formalized medical knowledge efficiently in the semantic web, and gave a front-end decision on antibiotics' suggestion for UTI.
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Affiliation(s)
- Elpiniki I Papageorgiou
- Department of Computer Engineering, Technological Educational Institute of Central Greece, 3rd Km Old National Road Lamia-Athens, 35100 Lamia, Greece.
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