Machine learning approach for sudden cardiac arrest prediction based on optimal heart rate variability features

Journal of Medical Imaging and Health Informatics

Volumn 4, Issue 4, 2014, Pages 521-532

  Murukesan, L ^a   Murugappan, M ^a   Iqbal, M ^a   Saravanan, K ^b  

^a UNIVERSITY MALAYSIA PERLIS   (Malaysia)

^b HOSPITAL PULAU PINANG   (Malaysia)

Author keywords

Analysis of Variance; Heart Rate Variability; Probabilistic Neural Network; Sequential Feature Selection; Sudden Cardiac Arrest; Support Vector Machine

Indexed keywords

ARTICLE; CARDIAC PATIENT; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; COMPARATIVE EFFECTIVENESS; COMPUTER ASSISTED DIAGNOSIS; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; EXTRASYSTOLE; FEMALE; HEART RATE VARIABILITY; HUMAN; MACHINE LEARNING; MALE; NONLINEAR SYSTEM; PREDICTIVE VALUE; PROBABILISTIC NEURAL NETWORK; RR INTERVAL; SEQUENTIAL FEATURE SELECTION ALGORITHM; SIGNAL PROCESSING; SUDDEN CARDIAC DEATH; SUPPORT VECTOR MACHINE; WAVELET ANALYSIS;

EID: 84911405071     PISSN: 21567018     EISSN: 21567026     Source Type: Journal    
DOI: 10.1166/jmihi.2014.1287     Document Type: Article

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