Prediction of Health Outcomes Using Big (Health) Data

被引：0
|
作者：
Arandjelovic, Ognjen [1 ]
机构：
[1] Univ St Andrews, St Andrews KY16 9AJ, Fife, Scotland
来源：
2015 37TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) | 2015年
关键词：
D O I：
暂无
中图分类号：
R318 [生物医学工程];
学科分类号：
0831 ;
摘要：
The vast amounts of information in the form of electronic medical records are used to develop a novel model of disease progression. The proposed model is based on the representation of a patient's medical history in the form of a binary history vector, motivated by empirical evidence from previous work and validated using a large 'real-world' data corpus. The scope for the use of the described methodology is overarching and ranges from smarter allocation of resources and discovery of novel disease progression patterns and interactions, to incentivization of patients to make lifestyle changes.
引用
收藏
页码：2543 / 2546
页数：4
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