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Benis A, Min H, Gong Y, Biondich P, Robinson D, Law T, Nohr C, Faxvaag A, Rennert L, Hubig N, Gimbel R. Ontologies Applied in Clinical Decision Support System Rules: Systematic Review. JMIR Med Inform 2023; 11:e43053. [PMID: 36534739 PMCID: PMC9896360 DOI: 10.2196/43053] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/16/2022] [Accepted: 12/18/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Clinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused. OBJECTIVE Ontologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers of ontologies used in CDSS rules. METHODS The literature search was focused on the intersection of ontologies; clinical decision support; and rules in PubMed, the Association for Computing Machinery (ACM) Digital Library, and the Nursing & Allied Health Database. Grounded theory and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines were followed. One author initiated the screening and literature review, while 2 authors validated the processes and results independently. The inclusion and exclusion criteria were developed and refined iteratively. RESULTS CDSSs were primarily used to manage chronic conditions, alerts for medication prescriptions, reminders for immunizations and preventive services, diagnoses, and treatment recommendations among 81 included publications. The CDSS rules were presented in Semantic Web Rule Language, Jess, or Jena formats. Despite the fact that ontologies have been used to provide medical knowledge, CDSS rules, and terminologies, they have not been used in CDSS rule management or to facilitate the reuse of CDSS rules. CONCLUSIONS Ontologies have been used to organize and represent medical knowledge, controlled vocabularies, and the content of CDSS rules. So far, there has been little reuse of CDSS rules. More work is needed to improve the reusability and interoperability of CDSS rules. This review identified and described the ontologies that, despite their limitations, enable Semantic Web technologies and their applications in CDSS rules.
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Affiliation(s)
| | - Hua Min
- College of Public Health, George Mason University, Fairfax, VA, United States
| | - Yang Gong
- School of Biomedical Informatics, The University of Texas Health Sciences Center at Houston, Houston, TX, United States
| | - Paul Biondich
- Clem McDonald Biomedical Informatics Center, Regenstrief Institute, Indianapolis, IN, United States
| | | | - Timothy Law
- Ohio Musculoskeletal and Neurologic Institute, Ohio University, Athens, OH, United States
| | - Christian Nohr
- Department of Planning, Aalborg University, Aalborg, Denmark
| | - Arild Faxvaag
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
| | - Lior Rennert
- Department of Public Health Sciences, Clemson University, Clemson, SC, United States
| | - Nina Hubig
- School of Computing, Clemson University, Clemson, SC, United States
| | - Ronald Gimbel
- Department of Public Health Sciences, Clemson University, Clemson, SC, United States
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Yang Q, Luo T, Zhang W, Zhong X, He P, Zheng H. Data-driven treatment pathways mining for early breast cancer using cSPADE algorithm and system clustering. Int J Health Plann Manage 2022; 37:2569-2584. [PMID: 35445441 DOI: 10.1002/hpm.3483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 02/09/2022] [Accepted: 03/30/2022] [Indexed: 02/05/2023] Open
Abstract
OBJECTIVES Due to the multidimensional, multilayered, and chronological order of the cancer data, it was challenging for us to extract treatment paths. To determine whether the cSPADE algorithm and system clustering proposed in this study can effectively identify the treatment pathways for early breast cancer. METHODS We applied data mining technology to the electronic medical records of 6891 early breast cancer patients to mine treatment pathways. We provided a method of extracting data from EMR and performed three-stage mining: determining the treatment stage through the cSPADE algorithm → system clustering for treatment plan extraction → cSPADE mining sequence pattern for treatment. The Kolmogorov-Smirnov test and correlation analysis were used to cross-validate the sequence rules of early breast cancer treatment pathways. RESULTS We unearthed 55 sequence rules for early breast cancer treatment, 3 preoperative neoadjuvant chemotherapy regimens, three postoperative chemotherapy regimens, and 2 chemotherapy regimens for patients without surgery. Through 5-fold cross-validation, Pearson and Spearman correlation tests were performed. At the significance level of p < 0.05, all correlation coefficients of support, confidence and lift were greater than 0.89. Using the Kolmogorov-Smirnov test, we found no significant differences between the sequence distributions. CONCLUSIONS We have proved that cSPADE algorithm combined system clustering is an effective technique for identifying temporal relationships between treatment modalities, enabling hierarchical and vertical mining of breast cancer treatment models. In addition, we confirmed the robustness of the results by cross-validation of these treatment pathway ordering rules. Through this method, the treatment path of early breast cancer patients can be revealed, and the real-world breast cancer treatment behaviour model can be evaluated, which can provide reference for the redesign and optimization of treatment path.
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Affiliation(s)
- Qing Yang
- Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu, China
| | - Ting Luo
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Wei Zhang
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaorong Zhong
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.,Laboratory of Molecular Diagnosis of Cancer, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, China
| | - Ping He
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Hong Zheng
- Department of Head, Neck and Mammary Gland Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.,Laboratory of Molecular Diagnosis of Cancer, Clinical Research Center for Breast, West China Hospital, Sichuan University, Chengdu, China
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Dissanayake PI, Colicchio TK, Cimino JJ. Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis. J Am Med Inform Assoc 2020; 27:159-174. [PMID: 31592534 PMCID: PMC6913230 DOI: 10.1093/jamia/ocz169] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2019] [Revised: 07/20/2019] [Accepted: 09/05/2019] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE The study sought to describe the literature describing clinical reasoning ontology (CRO)-based clinical decision support systems (CDSSs) and identify and classify the medical knowledge and reasoning concepts and their properties within these ontologies to guide future research. METHODS MEDLINE, Scopus, and Google Scholar were searched through January 30, 2019, for studies describing CRO-based CDSSs. Articles that explored the development or application of CROs or terminology were selected. Eligible articles were assessed for quality features of both CDSSs and CROs to determine the current practices. We then compiled concepts and properties used within the articles. RESULTS We included 38 CRO-based CDSSs for the analysis. Diversity of the purpose and scope of their ontologies was seen, with a variety of knowledge sources were used for ontology development. We found 126 unique medical knowledge concepts, 38 unique reasoning concepts, and 240 unique properties (137 relationships and 103 attributes). Although there is a great diversity among the terms used across CROs, there is a significant overlap based on their descriptions. Only 5 studies described high quality assessment. CONCLUSION We identified current practices used in CRO development and provided lists of medical knowledge concepts, reasoning concepts, and properties (relationships and attributes) used by CRO-based CDSSs. CRO developers reason that the inclusion of concepts used by clinicians' during medical decision making has the potential to improve CDSS performance. However, at present, few CROs have been used for CDSSs, and high-quality studies describing CROs are sparse. Further research is required in developing high-quality CDSSs based on CROs.
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Affiliation(s)
| | - Tiago K Colicchio
- Informatics Institute, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - James J Cimino
- Informatics Institute, University of Alabama at Birmingham, Birmingham, Alabama, USA
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Cho M, Kim K, Lim J, Baek H, Kim S, Hwang H, Song M, Yoo S. Developing data-driven clinical pathways using electronic health records: The cases of total laparoscopic hysterectomy and rotator cuff tears. Int J Med Inform 2019; 133:104015. [PMID: 31683142 DOI: 10.1016/j.ijmedinf.2019.104015] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 07/26/2019] [Accepted: 10/15/2019] [Indexed: 02/01/2023]
Abstract
OBJECTIVE A clinical pathway is one of the tools used to support clinical decision making that provides a standardized care process in a specific context. The objective of this research was to develop a method for building data-driven clinical pathways using electronic health record data. MATERIALS AND METHODS We proposed a matching rate-based clinical pathway mining algorithm that produces the optimal set of clinical orders for each clinical stage by employing matching rates. To validate the approach, we utilized two different datasets of deidentified inpatient records directly related to total laparoscopic hysterectomy (TLH) and rotator cuff tears (RCTs) from a hospital in South Korea. The derived data-driven clinical pathways were evaluated with knowledge-based models by health professionals using a delta analysis. RESULTS Two different data-driven clinical pathways, i.e., TLH and RCTs, were produced by applying the matching rate-based clinical pathway mining algorithm. We identified that there were significant differences in clinical orders between the data-driven and knowledge-based models. Additionally, the data-driven clinical pathways based on our algorithm outperformed the models by clinical experts, with average matching rates of 82.02% and 79.66%, respectively. CONCLUSION The proposed algorithm will be helpful for supporting clinical decisions and directly applicable in medical practices.
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Affiliation(s)
- Minsu Cho
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, South Korea
| | - Kidong Kim
- Department of Obstetrics and Gynecology, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Jungeun Lim
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, South Korea
| | - Hyunyoung Baek
- Office of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Seok Kim
- Office of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Hee Hwang
- Office of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Minseok Song
- Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, South Korea.
| | - Sooyoung Yoo
- Office of eHealth Research and Businesses, Seoul National University Bundang Hospital, Seongnam, South Korea.
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Jimenez-Molina A, Gaete-Villegas J, Fuentes J. ProFUSO: Business process and ontology-based framework to develop ubiquitous computing support systems for chronic patients' management. J Biomed Inform 2018; 82:106-127. [PMID: 29627462 DOI: 10.1016/j.jbi.2018.04.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2017] [Revised: 03/29/2018] [Accepted: 04/03/2018] [Indexed: 01/20/2023]
Abstract
New advances in telemedicine, ubiquitous computing, and artificial intelligence have supported the emergence of more advanced applications and support systems for chronic patients. This trend addresses the important problem of chronic illnesses, highlighted by multiple international organizations as a core issue in future healthcare. Despite the myriad of exciting new developments, each application and system is designed and implemented for specific purposes and lacks the flexibility to support different healthcare concerns. Some of the known problems of such developments are the integration issues between applications and existing healthcare systems, the reusability of technical knowledge in the creation of new and more sophisticated systems and the usage of data gathered from multiple sources in the generation of new knowledge. This paper proposes a framework for the development of chronic disease support systems and applications as an answer to these shortcomings. Through this framework our pursuit is to create a common ground methodology upon which new developments can be created and easily integrated to provide better support to chronic patients, medical staff and other relevant participants. General requirements are inferred for any support system from the primary attention process of chronic patients by the Business Process Management Notation. Numerous technical approaches are proposed to design a general architecture that considers the medical organizational requirements in the treatment of a patient. A framework is presented for any application in support of chronic patients and evaluated by a case study to test the applicability and pertinence of the solution.
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Affiliation(s)
- Angel Jimenez-Molina
- Department of Industrial Engineering, University of Chile, Beauchef 851, Santiago 8370456, Chile.
| | - Jorge Gaete-Villegas
- Department of Industrial Engineering, University of Chile, Beauchef 851, Santiago 8370456, Chile.
| | - Javier Fuentes
- Department of Industrial Engineering, University of Chile, Beauchef 851, Santiago 8370456, Chile.
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Zhang YF, Gou L, Zhou TS, Lin DN, Zheng J, Li Y, Li JS. An ontology-based approach to patient follow-up assessment for continuous and personalized chronic disease management. J Biomed Inform 2017; 72:45-59. [PMID: 28676255 DOI: 10.1016/j.jbi.2017.06.021] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2017] [Revised: 06/23/2017] [Accepted: 06/30/2017] [Indexed: 01/22/2023]
Abstract
OBJECTIVE Chronic diseases are complex and persistent clinical conditions that require close collaboration among patients and health care providers in the implementation of long-term and integrated care programs. However, current solutions focus partially on intensive interventions at hospitals rather than on continuous and personalized chronic disease management. This study aims to fill this gap by providing computerized clinical decision support during follow-up assessments of chronically ill patients at home. METHODS We proposed an ontology-based framework to integrate patient data, medical domain knowledge, and patient assessment criteria for chronic disease patient follow-up assessments. A clinical decision support system was developed to implement this framework for automatic selection and adaptation of standard assessment protocols to suit patient personal conditions. We evaluated our method in the case study of type 2 diabetic patient follow-up assessments. RESULTS The proposed framework was instantiated using real data from 115,477 follow-up assessment records of 36,162 type 2 diabetic patients. Standard evaluation criteria were automatically selected and adapted to the particularities of each patient. Assessment results were generated as a general typing of patient overall condition and detailed scoring for each criterion, providing important indicators to the case manager about possible inappropriate judgments, in addition to raising patient awareness of their disease control outcomes. Using historical data as the gold standard, our system achieved a rate of accuracy of 99.93% and completeness of 95.00%. CONCLUSIONS This study contributes to improving the accessibility, efficiency and quality of current patient follow-up services. It also provides a generic approach to knowledge sharing and reuse for patient-centered chronic disease management.
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Affiliation(s)
- Yi-Fan Zhang
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Ling Gou
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Tian-Shu Zhou
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - De-Nan Lin
- Health Information Center, Shenzhen, China
| | - Jing Zheng
- Health Information Center, Shenzhen, China
| | - Ye Li
- Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jing-Song Li
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
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Scientific and Clinical Abstracts From the 2016 WOCN® Society & CAET Joint Conference. J Wound Ostomy Continence Nurs 2016. [DOI: 10.1097/won.0000000000000226] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Design and Development of a Sharable Clinical Decision Support System Based on a Semantic Web Service Framework. J Med Syst 2016; 40:118. [PMID: 27002818 DOI: 10.1007/s10916-016-0472-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2015] [Accepted: 03/07/2016] [Indexed: 12/24/2022]
Abstract
Clinical decision support (CDS) systems provide clinicians and other health care stakeholders with patient-specific assessments or recommendations to aid in the clinical decision-making process. Despite their demonstrated potential for improving health care quality, the widespread availability of CDS systems has been limited mainly by the difficulty and cost of sharing CDS knowledge among heterogeneous healthcare information systems. The purpose of this study was to design and develop a sharable clinical decision support (S-CDS) system that meets this challenge. The fundamental knowledge base consists of independent and reusable knowledge modules (KMs) to meet core CDS needs, wherein each KM is semantically well defined based on the standard information model, terminologies, and representation formalisms. A semantic web service framework was developed to identify, access, and leverage these KMs across diverse CDS applications and care settings. The S-CDS system has been validated in two distinct client CDS applications. Model-level evaluation results confirmed coherent knowledge representation. Application-level evaluation results reached an overall accuracy of 98.66 % and a completeness of 96.98 %. The evaluation results demonstrated the technical feasibility and application prospect of our approach. Compared with other CDS engineering efforts, our approach facilitates system development and implementation and improves system maintainability, scalability and efficiency, which contribute to the widespread adoption of effective CDS within the healthcare domain.
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Wang HQ, Zhou TS, Zhang YF, Chen L, Li JS. Research and Development of Semantics-based Sharable Clinical Pathway Systems. J Med Syst 2015; 39:73. [PMID: 26071207 DOI: 10.1007/s10916-015-0257-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2014] [Accepted: 06/02/2015] [Indexed: 12/14/2022]
Abstract
The clinical pathway (CP) as a novel medical management schema is beneficial for reducing the length of stay, decreasing heath care costs, standardizing clinical activities, and improving medical quality. However, the practicability of CPs is limited by the complexity and expense of adding the standard functions of electronic CPs to existing electronic medical record (EMR) systems. The purpose of this study was to design and develop an independent clinical pathway (ICP) system that is sharable with different EMR systems. An innovative knowledge base pattern was designed with separate namespaces for global knowledge, local knowledge, and real-time instances. Semantic web technologies were introduced to support knowledge sharing and intelligent reasoning. The proposed system, which was developed in a Java integrated development environment, achieved standard functions of electronic CPs without modifying existing EMR systems and integration environments in hospitals. The interaction solution between the pathway system and the EMR system simplifies the integration procedures with other hospital information systems. Five categories of transmission information were summarized to ensure the interaction process. Detailed procedures for the application of CPs to patients and managing exceptional alerts are presented by explicit data flow analysis. Compared to embedded pathway systems, independent pathway systems feature greater feasibility and practicability and are more advantageous for achieving the normalized management of standard CPs.
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Affiliation(s)
- Hua-Qiong Wang
- Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
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März K, Hafezi M, Weller T, Saffari A, Nolden M, Fard N, Majlesara A, Zelzer S, Maleshkova M, Volovyk M, Gharabaghi N, Wagner M, Emami G, Engelhardt S, Fetzer A, Kenngott H, Rezai N, Rettinger A, Studer R, Mehrabi A, Maier-Hein L. Toward knowledge-based liver surgery: holistic information processing for surgical decision support. Int J Comput Assist Radiol Surg 2015; 10:749-59. [PMID: 25847671 DOI: 10.1007/s11548-015-1187-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2015] [Accepted: 03/20/2015] [Indexed: 11/27/2022]
Abstract
PURPOSE Malignant neoplasms of the liver are among the most frequent cancers worldwide. Given the diversity of options for liver cancer therapy, the choice of treatment depends on various parameters including patient condition, tumor size and location, liver function, and previous interventions. To address this issue, we present the first approach to treatment strategy planning based on holistic processing of patient-individual data, practical knowledge (i.e., case knowledge), and factual knowledge (e.g., clinical guidelines and studies). METHODS The contributions of this paper are as follows: (1) a formalized dynamic patient model that incorporates all the heterogeneous data acquired for a specific patient in the whole course of disease treatment; (2) a concept for formalizing factual knowledge; and (3) a technical infrastructure that enables storing, accessing, and processing of heterogeneous data to support clinical decision making. RESULTS Our patient model, which currently covers 602 patient-individual parameters, was successfully instantiated for 184 patients. It was sufficiently comprehensive to serve as the basis for the formalization of a total of 72 rules extracted from studies on patients with colorectal liver metastases or hepatocellular carcinoma. For a subset of 70 patients with these diagnoses, the system derived an average of [Formula: see text] assertions per patient. CONCLUSION The proposed concept paves the way for holistic treatment strategy planning by enabling joint storing and processing of heterogeneous data from various information sources.
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Affiliation(s)
- K März
- Department of Medical and Biological Informatics, German Cancer Research Center, Heidelberg, Germany,
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