Complex data-driven predictive modeling in personalized clinical decision support for Acute Coronary Syndrome episodes

被引：21

作者：

Krikunov, Alexey V. ^{[1
]}

Bolgova, Ekaterina V. ^{[1
]}

Krotov, Evgeniy ^{[1
]}

Abuhay, Tesfamariam M. ^{[1
]}

Yakovlev, Alexey N. ^{[1
,2
]}

Kovalchuk, Sergey V. ^{[1
]}

机构：

[1] ITMO Univ, St Petersburg, Russia

[2] Fed Almazov North West Med Res Ctr, St Petersburg, Russia

来源：

INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE 2016 (ICCS 2016) | 2016年 / 80卷

基金：

俄罗斯科学基金会;

关键词：

data-driven modeling; decision support system; clinical DSS; personalized medicine; p4; medicine; ELECTRONIC HEALTH RECORDS;

D O I：

10.1016/j.procs.2016.05.332

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The objective of this paper is to demonstrate the development of complex model of clinical episode, based on data-driven approach, for decision support in treatment of ACS (Acute Coronary Syndrome). The idea is aimed at improving predictive capability of a data-driven model by combining different models within a composite data-driven model. It can be implemented either hierarchical or alternative combination of models. Three examples of data-driven models are described: simple classifier, outcome prediction based on reanimation time and states based prediction model, to be used as part of complex model of episodes. To implement the proposed approach, a generalized architecture of data-driven clinical decision support systems was developed. The solution is developed as a part of complex clinical decision support system for cardiac diseases for Federal Almazov North-West Medical Research Centre in Saint Petersburg, Russia.

引用

页码：518 / 529

页数：12

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