Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection

Expert Systems with Applications

Volumn 39, Issue 2, 2012, Pages 1956-1967

  Alonso Atienza, Felipe ^a   Rojo Álvarez, José Luis ^a   Rosado Muñoz, Alfredo ^b   Vinagre, Juan J ^a   García Alberola, Arcadi ^c   Camps Valls, Gustavo ^b  

^a UNIVERSIDAD REY JUAN CARLOS   (Spain)

^b UNIVERSITY OF VALENCIA   (Spain)

^c HOSPITAL UNIVERSITARIO VIRGEN DE LA ARRIXACA   (Spain)

Author keywords

Arrhythmia classification; Bootstrap; Feature selection; Support vector machines; Ventricular fibrillation detection

Indexed keywords

ARRHYTHMIA CLASSIFICATION; AUTOMATIC DEVICE; BOOTSTRAP; BOOTSTRAP METHOD; BOOTSTRAP RESAMPLING; DETECTION EFFICIENCY; DETECTOR PERFORMANCE; DIFFERENT DOMAINS; EARLY DETECTION; ECG PARAMETERS; EFFICIENT FEATURE SELECTIONS; FEATURE SETS; INPUT SPACE; MACHINE-LEARNING; NON-PARAMETRIC STATISTICS; RECURSIVE FEATURE ELIMINATION; SIMULATION STUDIES; SUPPORT VECTOR; TIME FREQUENCY; TIME-FREQUENCY PARAMETER; VENTRICULAR FIBRILLATION; VENTRICULAR FIBRILLATION DETECTION;

DETECTORS; ELECTROCARDIOGRAPHY; ELECTROCHROMIC DEVICES; LEARNING ALGORITHMS; SUPPORT VECTOR MACHINES;

FEATURE EXTRACTION;

EID: 80054911546     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.08.051     Document Type: Conference Paper

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