Computers in Cardiology / Physionet Challenge 2009: Predicting acute hypotensive episodes

Author

Jousset, F. ; Lemay, M. ; Vesin, JM

Author_Institution

Lab. de Traitement des Signaux 1, EPFL, Lausanne, Switzerland

fYear

2009

fDate

13-16 Sept. 2009

Firstpage

637

Lastpage

640

Abstract

The goal of the Computers in Cardiology/Physionet Challenge 2009 is to predict which patients will experience acute hypotensive episode within a forecast window of one hour. In our study, statistically robust features extracted from the supplied training set were defined. A Support Vector Machine was used to classify these features. In this paper, we present our method, results and conclusion about this statistical approach.

Keywords

blood pressure measurement; blood vessels; cardiology; feature extraction; medical computing; statistical analysis; support vector machines; Physionet challenge; acute hypotensive episodes; cardiology; forecast window; statistical approach; statistically robust feature extraction; support vector machine; time 1 h; training set; Arterial blood pressure; Bayesian methods; Cardiology; Computer architecture; Feature extraction; Hydrogen; Neural networks; Robustness; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Computers in Cardiology, 2009

Conference_Location

Park City, UT

ISSN

0276-6547

Print_ISBN

978-1-4244-7281-9

Electronic_ISBN

0276-6547

Type

conf

Filename

5445304

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2037863