ECG arrhythmia classification based on optimum-path forest

Expert Systems with Applications

Volumn 40, Issue 9, 2013, Pages 3561-3573

  Luz, Eduardo José Da S ^a   Nunes, Thiago M ^b   De Albuquerque, Victor Hugo C ^c   Papa, João P ^d   Menotti, David ^a  

^a FEDERAL UNIVERSITY OF OURO PRETO   (Brazil)

^b FEDERAL UNIVERSITY OF CEARÁ   (Brazil)

^c UNIVERSITY OF FORTALEZA   (Brazil)

^d SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

Author keywords

Bayesian; ECG classification; Feature extraction; Multilayer artificial neural network; Optimum path forest; Support vector machine

Indexed keywords

ARRHYTHMIA CLASSIFICATION; BAYESIAN; BAYESIAN CLASSIFIER; CARDIAC ARRHYTHMIA; CARDIAC RHYTHMS; CLASSIFICATION TIME; COMPUTATIONAL COSTS; ECG CLASSIFICATIONS; ELECTROCARDIOGRAM SIGNAL; EVALUATION PROTOCOL; FEATURE EXTRACTION AND CLASSIFICATION; GRAPH-BASED; HEART DISEASE DIAGNOSIS; HEARTBEAT SIGNALS; MEDICAL INSTRUMENTATION; MULTILAYER ARTIFICIAL NEURAL NETWORKS; OPTIMUM-PATH FORESTS; PATTERN RECOGNITION TECHNIQUES; ROBUST PERFORMANCE; SIGNAL CLASSIFICATION; SVM CLASSIFIERS; TRAINING AND TESTING;

DISEASES; EXPERT SYSTEMS; FEATURE EXTRACTION; FORESTRY; MULTILAYERS; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

ELECTROCARDIOGRAPHY;

DISEASES; EXPERT SYSTEMS; FORESTRY; MULTILAYERS; NEURAL NETWORKS;

EID: 84874665471     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2012.12.063     Document Type: Article

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