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Shafiee F, Sarbaz M, Marouzi P, Banaye Yazdipour A, Kimiafar K. Providing a framework for evaluation disease registry and health outcomes Software: Updating the CIPROS checklist. J Biomed Inform 2024; 149:104574. [PMID: 38101688 DOI: 10.1016/j.jbi.2023.104574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/27/2023] [Accepted: 12/08/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND AND AIMS Properly designed and implemented registry systems play an important role in improving health outcomes and reducing care costs, and can provide a true representation of clinical practice, disease outcomes, safety, and efficacy. Therefore, the aim of this study was to redesign and develop a checklist with items for a patient registry software system (CIPROS) Checklist. METHOD The study is descriptive-cross-sectional. The extraction of the data elements of the checklist was first done through a comprehensive review of the texts in PubMed, Science Direct and Scopus databases and receiving articles related to the evaluation of registry systems. Based on the extracted data, a five-point Likert scale questionnaire was created and 30 experts in this field were asked for their opinions using the two-step Delphi method. RESULTS A total of 100 information items were determined as a registry software evaluation checklist. This checklist included 12 groups of software architecture factors, development, interfaces and interactivity, semantics and standardization, internationality, data management, data quality and usability, data analysis, security, privacy, organizational, education and public factors. CONCLUSION By using the results of this research, it is possible to identify the defects and possible strengths of the registry software and put it at the disposal of the relevant officials to make a decision in this field. In this way, among the designers and developers of these softwares, the best and most appropriate ones are selected with the needs of the registry programs.
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Affiliation(s)
- Fatemeh Shafiee
- Department of Health Information Technology, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Masoume Sarbaz
- Department of Health Information Technology, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Parviz Marouzi
- Department of Health Information Technology, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Alireza Banaye Yazdipour
- Department of Health Information Technology, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran; Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran; Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran.
| | - Khalil Kimiafar
- Department of Health Information Technology, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
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Ruseckaite R, Caruso M, Mudunna C, Helwani F, Millis N, Ahern S. Informing a national rare disease registry strategy in Australia: a mixed methods study. BMC Health Serv Res 2023; 23:1187. [PMID: 37907945 PMCID: PMC10619239 DOI: 10.1186/s12913-023-10049-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 09/20/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Rare disease registries (RDRs) facilitate monitoring of rare diseases by pooling small datasets to increase clinical and epidemiological knowledge of rare diseases and promote patient centred best practice. The aim of this study was to understand the current state of RDRs in Australia, data captured, impact on patient outcomes, funding models, and barriers and enablers regarding their establishment and maintenance. METHODS An exploratory sequential mixed methods study design was adopted. First, a list of Australian RDRs, primary contacts and data custodians was generated through online and consumer group (Rare Voices Australia (RVA)) contacts. A cross-sectional, anonymous online survey was distributed to registry custodians, managers, or principal investigators of 74 identified Australian RDRs, 88 RVA Partners, 17 pharmaceutical organizations and 12 RVA Scientific and Medical Advisory Committee members. Next, managers and coordinators of RDRs and databases who participated in the survey were invited to participate in semi-structured interviews. Quantitative and qualitative data were analysed using basic descriptive statistics and content analysis, respectively. RESULTS Forty RDRs responded to the survey; nine were national, five were based in Australia and New Zealand, and the remaining were global. Of the 40 survey respondents, eight were interviewed. Most of the RDRs captured similar information regarding patient characteristics, comorbidities and clinical features, diagnosis, family history, genetic testing, procedures or treatment types, response to treatments and complications of treatments. Better treatment outcomes, changes in process of care and changes in quality of care were the most frequently reported benefits of the RDRs. The main challenges proved to be cost/funding of data collection, data completeness, and patient consent. When asked, the participants identified opportunities and challenges regarding potential options to streamline RDRs in Australia in the future. CONCLUSION Findings from this study highlighted significant dataset heterogeneity based on the individual disease, and current lack of interoperability and coordination between different existing RDRs in Australia. Nevertheless, a nationally coordinated approach to RDRs should be investigated given the particular benefits RDRs offer, such as access to research and the monitoring of new disease-modifying treatments.
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Affiliation(s)
- Rasa Ruseckaite
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
- School of Public Health and Preventive Medicine, Monash University, Victoria, 3004, Australia.
| | - Marisa Caruso
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - Chethana Mudunna
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | | | | | - Susannah Ahern
- Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
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Lazem M, Sheikhtaheri A. Barriers and facilitators for disease registry systems: a mixed-method study. BMC Med Inform Decis Mak 2022; 22:97. [PMID: 35410297 PMCID: PMC9004114 DOI: 10.1186/s12911-022-01840-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 04/05/2022] [Indexed: 11/17/2022] Open
Abstract
Background A Disease Registry System (DRS) is a system that collects standard data on a specific disease with an organized method for specific purposes in a population. Barriers and facilitators for DRSs are different according to the health system of each country, and identifying these factors is necessary to improve DRSs, so the purpose of this study was to identify and prioritize these factors. Methods First, by conducting 13 interviews with DRS specialists, barriers and facilitators for DRSs were identified and then, a questionnaire was developed to prioritize these factors. Then, 15 experts answered the questionnaires. We prioritized these factors based on the mean of scores in four levels including first priority (3.76–5), second priority (2.51–3.75), third priority (1.26–2.50), and the fourth priority (1–1.25). Results At first, 139 unique codes (63 barriers and 76 facilitators) were extracted from the interviews. We classified barriers into 9 themes, including management problems (24 codes), data collection-related problems (8 codes), poor cooperation/coordination (7 codes), technological problems and lack of motivation/interest (6 codes for each), threats to ethics/data security/confidentiality (5 codes), data quality-related problems (3 codes), limited patients’ participation and lack of or non-use of standards (2 codes for each). We also classified facilitators into 9 themes including management facilitators (36 codes), improving data quality (8 codes), proper data collection and observing ethics/data security/confidentiality (7 codes for each), appropriate technology (6 codes), increasing patients’ participation, increasing motivation/interest, improving cooperation/coordination, and the use of standards (3 codes for each). The first three ranked barriers based on mean scores included poor stakeholder cooperation/coordination (4.30), lack of standards (4.26), and data quality-related problems (4.06). The first three ranked facilitators included improving data quality (4.54), increasing motivation/interest (4.48), and observing ethics/data security/confidentiality (4.36). Conclusion Stakeholders’ coordination, proper data management, standardization and observing ethics, security/confidentiality are the most important areas for planning and investment that managers must consider for the continuation and success of DRSs. Supplementary Information The online version contains supplementary material available at 10.1186/s12911-022-01840-7.
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Affiliation(s)
- Mina Lazem
- Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Abbas Sheikhtaheri
- Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
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Lazem M, Sheikhtaheri A. Barriers and facilitators for the implementation of health condition and outcome registry systems: a systematic literature review. J Am Med Inform Assoc 2022; 29:723-734. [PMID: 35022765 PMCID: PMC8922163 DOI: 10.1093/jamia/ocab293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 09/29/2021] [Accepted: 12/27/2021] [Indexed: 01/13/2023] Open
Abstract
OBJECTIVE Health condition and outcome registry systems (registries) are used to collect data related to diseases and other health-related outcomes in specific populations. The implementation of these programs encounters various barriers and facilitators. Therefore, the present review aimed to identify and classify these barriers and facilitators. MATERIALS AND METHODS Some databases, including PubMed, Embase, ISI Web of Sciences, Cochrane Library, Scopus, Ovid, ProQuest, and Google Scholar, were searched using related keywords. Thereafter, based on the inclusion and exclusion criteria, the required data were collected using a data extraction form and then analyzed by the content analysis method. The obtained data were analyzed separately for research and review studies, and the developed and developing countries were compared. RESULTS Forty-five studies were reviewed and 175 unique codes were identified, among which 93 barriers and 82 facilitators were identified. Afterward, these factors were classified into the following 7 categories: barriers/facilitators to management and data management, poor/improved collaborations, technological constraints/appropriateness, barriers/facilitators to legal and regulatory factors, considerations/facilitators related to diseases, and poor/improved patients' participation. Although many of these factors have been more cited in the literature related to the developing countries, they were found to be common in both developed and developing countries. CONCLUSION Lack of budget, poor performance of managers, low data quality, and low stakeholders' interest/motivation on one hand, and financing, providing adequate training, ensuring data quality, and appropriate data collection on the other hand were found as the most common barriers or facilitators for the success of the registry implementation.
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Affiliation(s)
- Mina Lazem
- Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Abbas Sheikhtaheri
- Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran,Health Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran,Corresponding Author: Abbas Sheikhtaheri, PhD, Health Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Yasemi St, Valiasr Ave, Tehran, Iran;
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Musculoskeletal Tumor Registry, Time to Act and Take Steps Forward. INTERNATIONAL JOURNAL OF CANCER MANAGEMENT 2021. [DOI: 10.5812/ijcm.119280] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Khanali J, Kolahi AA. National and Subnational Cancer Incidence for 22 Cancer Groups, 2000 to 2016: A Study Based on Cancer Registration Data of Iran. J Cancer Epidemiol 2021; 2021:6676666. [PMID: 34335766 PMCID: PMC8292090 DOI: 10.1155/2021/6676666] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 05/10/2021] [Accepted: 06/29/2021] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Cancer is an increasing public health concern, and detailed knowledge of the cancer incidence is required for developing effective cancer control plans. The objective of this study is to present the cancer incidence of 22 cancer groups in Iran and all 31 provinces of the country from 2000 to 2016, for both sexes across different age groups. METHOD To study the national and provincial cancer incidence in Iran, we extracted data from the Cancer Project, which collects the Iranian cancer registry data and visualizes it in the VIZIT data visualization system. The methodology and statistical analysis that is used in this study follow the cancer project study protocol. Joinpoint analysis was performed to calculate the average annual percent change of the crude rates and age-standardized rates from 2000 to 2016. RESULTS Cancer incidence was 126,982 patients in 2016, and the crude rate (CR) of cancer in both sexes and all ages was 155 per 100,000 people. Cancer incidence approximately doubled between 2000 and 2016; however, the age-standardized rate (ASR) had a less drastic increase. The most incident cancers in 2016 were breast, skin, and colorectal cancers; however, the ranking of cancer groups by incidence was different in different age and sex groups and provinces. Some cancers exhibited a unique distribution pattern in the country with high-incidence local areas. Discussion. The study showed that cancer incidence, crude rate, and age-standardized rate (ASR) in Iran had increased in 2000-2016 with vast heterogeneity by cancer type, province, and sex. Moreover, it was shown that the crude rate of cancer in Iran was much less than the global cancer crude rate. Providing such data helps to allocate resources and develop effective national cancer control plans appropriately.
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Affiliation(s)
- Javad Khanali
- Social Determinants of Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ali-Asghar Kolahi
- Social Determinants of Health Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Lazem M, Sheikhtaheri A, Hooman N. Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation. Orphanet J Rare Dis 2021; 16:240. [PMID: 34034793 PMCID: PMC8146148 DOI: 10.1186/s13023-021-01871-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 05/14/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Hemolytic uremic syndrome (HUS) is a rare condition which diagnosed with the triad of thrombocytopenia, microangiopathic hemolytic anemia, and acute renal injury. There is a high requirement for research to discover treatments. HUS registries can be used as an important information infrastructure. In this study, we identified and compared the different features of HUS registries to present a guide for the development and implementation of HUS registries. RESULTS The purposes of registries were classified as clinical (9 registries), research (7 registries), and epidemiological (5 registries), and only 3 registries pursued all three types of purposes. The data set included demographic data, medical and family history, para-clinical and diagnostic measures, treatment and pharmacological data, complications, and outcomes. The assessment strategies of data quality included monthly evaluation and data audit, the participation of physicians to collect data, editing and correcting data errors, increasing the rate of data completion, following guidelines and data quality training, using specific data quality indicators, and real-time evaluation of data at the time of data entry. 8 registries include atypical HUS patients, and 7 registries include all patients regardless of age. Only two registries focused on children. 4 registries apply prospective and 4 applied both prospective, and retrospective data collection. Finally, specialized hospitals were the main data source for these registries. CONCLUSION Based on the findings, we suggested a learning framework for developing and implementing an HUS registry. This framework includes lessons learned and suggestions for HUS registry purposes, minimum data set, data quality assurance, data collection methods, inclusion and exclusion criteria as well as data sources. This framework can help researchers develop HUS registries.
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Affiliation(s)
- Mina Lazem
- Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
| | - Abbas Sheikhtaheri
- Health Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran.
| | - Nakysa Hooman
- Pediatric Nephrology Department, Aliasghar Clinical Research Development Center (AACRDC), Aliasghar Children Hospital, Iran University of Medical Sciences, Tehran, Iran
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Chen H, Yu P, Hailey D, Cui T. Validation of 4D Components for Measuring Quality of the Public Health Data Collection Process: Elicitation Study. J Med Internet Res 2021; 23:e17240. [PMID: 33970112 PMCID: PMC8145089 DOI: 10.2196/17240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 11/06/2020] [Accepted: 03/11/2021] [Indexed: 11/23/2022] Open
Abstract
Background Identification of the essential components of the quality of the data collection process is the starting point for designing effective data quality management strategies for public health information systems. An inductive analysis of the global literature on the quality of the public health data collection process has led to the formation of a preliminary 4D component framework, that is, data collection management, data collection personnel, data collection system, and data collection environment. It is necessary to empirically validate the framework for its use in future research and practice. Objective This study aims to obtain empirical evidence to confirm the components of the framework and, if needed, to further develop this framework. Methods Expert elicitation was used to evaluate the preliminary framework in the context of the Chinese National HIV/AIDS Comprehensive Response Information Management System. The research processes included the development of an interview guide and data collection form, data collection, and analysis. A total of 3 public health administrators, 15 public health workers, and 10 health care practitioners participated in the elicitation session. A framework qualitative data analysis approach and a quantitative comparative analysis were followed to elicit themes from the interview transcripts and to map them to the elements of the preliminary 4D framework. Results A total of 302 codes were extracted from interview transcripts. After iterative and recursive comparison, classification, and mapping, 46 new indicators emerged; 24.8% (37/149) of the original indicators were deleted because of a lack of evidence support and another 28.2% (42/149) were merged. The validated 4D component framework consists of 116 indicators (82 facilitators and 34 barriers). The first component, data collection management, includes data collection protocols and quality assurance. It was measured by 41 indicators, decreased from the original 49% (73/149) to 35.3% (41/116). The second component, data collection environment, was measured by 37 indicators, increased from the original 13.4% (20/149) to 31.9% (37/116). It comprised leadership, training, funding, organizational policy, high-level management support, and collaboration among parallel organizations. The third component, data collection personnel, includes the perception of data collection, skills and competence, communication, and staffing patterns. There was no change in the proportion for data collection personnel (19.5% vs 19.0%), although the number of its indicators was reduced from 29 to 22. The fourth component, the data collection system, was measured using 16 indicators, with a slight decrease in percentage points from 18.1% (27/149) to 13.8% (16/116). It comprised functions, system integration, technical support, and data collection devices. Conclusions This expert elicitation study validated and improved the 4D framework. The framework can be useful in developing a questionnaire survey instrument for measuring the quality of the public health data collection process after validation of psychometric properties and item reduction.
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Affiliation(s)
- Hong Chen
- School of Computing and Information Technology, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia.,Jiangxi Provincial Centre for Disease Control and Prevention, Nanchang, China
| | - Ping Yu
- School of Computing and Information Technology, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia.,Illawarra Health and Medical Research Institute, University of Wollongong, Wollongong, Australia
| | - David Hailey
- School of Computing and Information Technology, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, Australia
| | - Tingru Cui
- School of Computing and Information Systems, University of Melbourne, Melbourne, Australia
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Zarei J, Dastoorpoor M, Jamshidnezhad A, Cheraghi M, Sheikhtaheri A. Regional COVID-19 registry in Khuzestan, Iran: A study protocol and lessons learned from a pilot implementation. INFORMATICS IN MEDICINE UNLOCKED 2021; 23:100520. [PMID: 33495736 PMCID: PMC7816600 DOI: 10.1016/j.imu.2021.100520] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 01/14/2021] [Accepted: 01/14/2021] [Indexed: 02/08/2023] Open
Abstract
Disease registry systems provide a strong information infrastructure for decision-making and research. The purpose of this study is to describe the implementation method and protocol of the COVID-19 registry in Khuzestan province, Iran. We established a steering committee and formulated the purposes of the registry. Then, based on reviewing the literature, and expert panels, the minimum data set, the data collection forms and the web-based software were developed. Data collection is done retrospectively through Hospital Information Systems, Medical Care Monitoring Center system (MCMC), Management of Communicable Disease Prevention and Control system (MCDPC) as well as, patients' records. For prospective data collection, the data collection forms are compiled with patients' medical records by the medical staff and are then entered into the registry system. We collect patients' administrative and demographic data, history and physical examinations, test and imaging results, disease progression, treatment, outcomes, and follow-ups of the confirmed and suspected inpatients and outpatients. From April 20 to December 5, 2020, the data of 4,812 confirmed cases and 7,113 suspected cases were collected from two COVID-19 referral hospitals. Based on our experience, recording information along with providing care for patients and putting patients' data registration in the medical staff's routine, structuring data, having a flexible technical team and rapid software development for multiple and continuous updates, automating data collection by connecting the registry to existing information systems and having different incentives, the registration process can be strengthened.
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Affiliation(s)
- Javad Zarei
- Health Information Technology Department, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Maryam Dastoorpoor
- Department of Biostatistics and Epidemiology, Social Determinants of Health Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Amir Jamshidnezhad
- Health Information Technology Department, School of Allied Medical Sciences, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Maria Cheraghi
- Social Determinant of Health Research Center, Department of Public Health, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Abbas Sheikhtaheri
- Health Management and Economics Research Center, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
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Persistence of data-driven knowledge to predict breast cancer survival. Int J Med Inform 2019; 129:303-311. [DOI: 10.1016/j.ijmedinf.2019.06.018] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Revised: 06/05/2019] [Accepted: 06/20/2019] [Indexed: 11/23/2022]
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