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A belief rule-based decision support system for clinical risk assessment of cardiac chest pain
Kong, Guilan1; Xu, Dong-Ling2; Body, Richard3; Yang, Jian-Bo2; Mackway-Jones, Kevin4; Carley, Simon4
关键词Decision Support Systems Or In medicIne Uncertainty Modeling Belief Rule Base Evidential Reasoning Approach Clinical Risk Assessment
刊名EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
2012-06-16
DOI10.1016/j.ejor.2011.10.044
219期:3页:564-573
收录类别SCI
文章类型Article
WOS标题词Social Sciences ; Science & Technology
类目[WOS]Management ; Operations Research & Management Science
资助者UK Engineering and Physical Science Research Council (EPSRC) ; University of Manchester ; Natural Science Foundation of China ; Biomedical Research Centre at Manchester Royal Infirmary ; UK Engineering and Physical Science Research Council (EPSRC) ; University of Manchester ; Natural Science Foundation of China ; Biomedical Research Centre at Manchester Royal Infirmary
研究领域[WOS]Business & Economics ; Operations Research & Management Science
关键词[WOS]EVIDENTIAL REASONING APPROACH ; ACUTE MYOCARDIAL-INFARCTION ; ACUTE CORONARY SYNDROMES ; EMERGENCY-DEPARTMENT ; ROC-CURVE ; UNCERTAINTY ; DIAGNOSIS ; TECHNOLOGIES ; EXPERIENCE ; PROGRAM
英文摘要

This paper describes a prototype clinical decision support system (CDSS) for risk stratification of patients with cardiac chest pain. A newly developed belief rule-based inference methodology-RIMER was employed for developing the prototype. Based on the belief rule-based inference methodology, the prototype CDSS can deal with uncertainties in both clinical domain knowledge and clinical data. Moreover, the prototype can automatically update its knowledge base via a belief rule base (BRB) learning module which can adjust BRB through accumulated historical clinical cases. The domain specific knowledge used to construct the knowledge base of the prototype was learned from real patient data. We simulated a set of 1000 patients in cardiac chest pain to validate the prototype. The belief rule-based prototype CDSS has been found to perform extremely well. Firstly, the system can provide more reliable and informative diagnosis recommendations than manual diagnosis using traditional rules when there are clinical uncertainties. Secondly, the diagnostic performance of the system can be significantly improved after training the BRB through accumulated clinical cases. (C) 2011 Elsevier BY. All rights reserved.

语种英语
所属项目编号EP/F024606/1 ; KTA 031 ; 60736026 ; 70925004
资助者UK Engineering and Physical Science Research Council (EPSRC) ; University of Manchester ; Natural Science Foundation of China ; Biomedical Research Centre at Manchester Royal Infirmary ; UK Engineering and Physical Science Research Council (EPSRC) ; University of Manchester ; Natural Science Foundation of China ; Biomedical Research Centre at Manchester Royal Infirmary
WOS记录号WOS:000302199300008
引用统计
文献类型期刊论文
条目标识符http://ir.bjmu.edu.cn/handle/400002259/53610
专题北京大学医学信息学中心
作者单位1.Peking Univ, Med Informat Ctr, Beijing 100191, Peoples R China
2.Univ Manchester, Manchester Business Sch, Manchester M15 6PB, Lancs, England
3.Univ Manchester, Cardiovasc Sci Res Grp, Manchester M13 9WL, Lancs, England
4.Manchester Royal Infirm, Emergency Dept, Manchester M13 9WL, Lancs, England
推荐引用方式
GB/T 7714
Kong, Guilan,Xu, Dong-Ling,Body, Richard,et al. A belief rule-based decision support system for clinical risk assessment of cardiac chest pain[J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH,2012,219(3):564-573.
APA Kong, Guilan,Xu, Dong-Ling,Body, Richard,Yang, Jian-Bo,Mackway-Jones, Kevin,&Carley, Simon.(2012).A belief rule-based decision support system for clinical risk assessment of cardiac chest pain.EUROPEAN JOURNAL OF OPERATIONAL RESEARCH,219(3),564-573.
MLA Kong, Guilan,et al."A belief rule-based decision support system for clinical risk assessment of cardiac chest pain".EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 219.3(2012):564-573.
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