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Application and Exploration of Big Data Mining in Clinical Medicine

摘要Objective:To review theories and technologies of big data mining and their application in clinical medicine.Data Sources:Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015.Study Selection:Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected.Results:This review characterized the basic theories and technologies of big data mining including fuzzy theory,rough set theory,cloud theory,Dempster-Shafer theory,artificial neural network,genetic algorithm,inductive learning theory,Bayesian network,decision tree,pattern recognition,high-performance computing,and statistical analysis.The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment,clinical decision support,prediction of disease development,guidance of rational use of drugs,medical management,and evidence-based medicine.Conclusion:Big data mining has the potential to play an important role in clinical medicine.

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作者单位 Department of Cardiovascular Internal Medicine, Nanlou Branch of Chinese People's Liberation Army General Hospital, Beijing 100853, China [1] State Key Laboratory of Intelligent Control and Decision, School of Automation, Beijing Institute of Technology, Beijing 100081, China [2] Department of Cadre Physiotherapy, Chinese People's Liberation Army General Hospital, Beijing 100853, China [3]
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DOI 10.4103/0366-6999.178019
发布时间 2016-04-18(万方平台首次上网日期,不代表论文的发表时间)
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中华医学杂志(英文版)

中华医学杂志(英文版)

2016年129卷6期

731-738页

SCIMEDLINEISTICCSCDCABP

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