Hierarchical state space partitioning with a network self-organising map for the recognition of ST-T segment changes

Medical and Biological Engineering and Computing

Volumn 38, Issue 4, 2000, Pages 406-415

  Bezerianos, A ^a   Vladutu, L ^a   Papadimitriou, S ^a,b  

^a UNIVERSITY OF PATRAS   (Greece)

^b UNIVERSITY OF PATRAS   (Greece)

Author keywords

Automatic ischaemia detection; Learning vector quantisation; Multilayer perceptrons; Neural networks; Radiol basis functions; Self organising maps

Indexed keywords

MULTILAYER NEURAL NETWORKS; PATTERN RECOGNITION; STATE SPACE METHODS; VECTOR QUANTIZATION;

KOHONEN SELF-ORGANIZING MAP (SOM) MODEL; RADIAL BASIS FUNCTION (RBF);

ELECTROCARDIOGRAPHY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; DATA BASE; DEVICE; DIAGNOSTIC ACCURACY; EUROPE; HEART MUSCLE ISCHEMIA; MATHEMATICAL MODEL; PREDICTION; ST SEGMENT; T WAVE;

EID: 0034233598     PISSN: 01400118     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF02345010     Document Type: Article

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