A Hybrid System with Hidden Markov Models and Gaussian Mixture Models for Myocardial Infarction Classification with 12-Lead ECGs

2009 11th IEEE International Conference on High Performance Computing and Communications, HPCC 2009

Volumn , Issue , 2009, Pages 110-116

  Chang, Pei Chann ^a   Hsieh, Jui Chien ^a   Lin, Jyun Jie ^a   Chou, Yen Hung ^a   Liu, Chen Hao ^b  

^a YUAN ZE UNIVERSITY   (Taiwan)

^b KAINAN UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

A-DENSITY; ACCURACY RATE; CLINICAL DATA; DATA CLASSIFICATION; DIAGNOSIS SYSTEMS; ECG DATA; ECG SEGMENTATION; FEATURE VECTORS; GAUSSIAN MIXTURE MODEL; LOG LIKELIHOOD; MYOCARDIAL INFARCTION; PREDICTIVITY; STATISTICAL FEATURES;

COMPUTER SCIENCE; ELECTRIC GROUNDING; ELECTROCARDIOGRAPHY; ELECTROCHROMIC DEVICES; HYBRID COMPUTERS; HYBRID SYSTEMS; NORMAL DISTRIBUTION; OBJECT RECOGNITION;

HIDDEN MARKOV MODELS;

EID: 70449597283     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HPCC.2009.66     Document Type: Conference Paper

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