A Survey of Data Mining Technology on Electronic Medical Records

被引：0

作者：

Sun, Wencheng ^{[1
]}

Cai, Zhiping ^{[1
]}

Liu, Fang ^{[1
]}

Fang, Shengqun ^{[1
]}

Wang, Guoyan ^{[2
]}

机构：

[1] Natl Univ Def Technol, Coll Comp, Changsha 410073, Hunan, Peoples R China

[2] SysCan Biotechnol Co Ltd, Suzhou 215000, Peoples R China

来源：

2017 IEEE 19TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATIONS AND SERVICES (HEALTHCOM) | 2017年

关键词：

EMR; data mining; classification; clustering; regression;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Medical institutes use Electronic Medical Record (EMR) to record a series of medical events, including diagnostic information (diagnosis codes), procedures performed (procedure codes) and admission details. Plenty of data mining technologies are applied in the EMR data set for knowledge discovery, which is precious to medical practice. The knowledge found is conducive to develop treatment plans, improve health care and reduce medical expenses, moreover, it could also provide further assistance to predict and control outbreaks of epidemic disease. The growing social value it creates has made it a hot spot for experts and scholars. In this paper, we will summarize the research status of data mining technologies on EMR, and analyze the challenges that EMR research is confronting currently.

引用

页数：6

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