Machine Learning Methods for Mortality Prediction in Patients with ST Elevation Myocardial Infarction

0380997 - ÚTIA 2013 RIV CZ eng C - Conference Paper (international conference)
Vomlel, Jiří - Kružík, H. - Tůma, P. - Přeček, J. - Hutyra, M.
Machine Learning Methods for Mortality Prediction in Patients with ST Elevation Myocardial Infarction.
Proceedings of The Ninth Workshop on Uncertainty Processing. Prague: Faculty of Management, University of Economics, Prague, 2012 - (Kroupa, T.; Vejnarová, J.), s. 204-213. ISBN 978-80-245-1885-5.
[The Ninth Workshop on Uncertainty Processing. Mariánské Lázně (CZ), 12.09.2012-15.09.2012]
R&D Projects: GA ČR GA201/08/0539
Institutional support: RVO:67985556
Keywords : Machine Learning * Acute Myocardial Infarction * Mortality Prediction
Subject RIV: JD - Computer Applications, Robotics
http://library.utia.cas.cz/separaty/2012/MTR/vomlel-machine learning methods for mortality prediction in patients with st elevation myocardial infarction.pdf

ST Elevation Myocardial Infarction (STEMI) is the leading cause of death in developed countries. The objective of our research is to design and verify a predictive model of hospital mortality in STEMI based on clinical data about patients that could serve as a benchmark for evaluation of healthcare providers. In this paper we present results of an experimental evaluation of different machine learning methods on a real data about 603 patients from University Hospital in Olomouc.
Permanent Link: http://hdl.handle.net/11104/0211570