Complex Data-driven Predictive Modeling in Personalized Clinical Decision Support for Acute Coronary Syndrome Episodes | Zendy

Alexey V. Krikunov | Zendy; Ekaterina Bolgova | Zendy; Evgeniy Krotov | Zendy; Tesfamariam M. Abuhay | Zendy; A. N. Yakovlev | Zendy; Sergey V. Kovalchuk | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Complex Data-driven Predictive Modeling in Personalized Clinical Decision Support for Acute Coronary Syndrome Episodes

Author(s) -

Alexey V. Krikunov,

Ekaterina Bolgova,

Evgeniy Krotov,

Tesfamariam M. Abuhay,

A. N. Yakovlev,

Sergey V. Kovalchuk

Publication year - 2016

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2016.05.332

Subject(s) - computer science , acute coronary syndrome , clinical decision support system , decision support system , predictive modelling , classifier (uml) , data mining , machine learning , decision model , artificial intelligence , data modeling , medicine , database , myocardial infarction

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

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research