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Hierarchical State Space Partitioning with the Network Self-Organizing Map for the effective recognition of the ST-T Segment Change

Domenii publicaţii > Ştiinţe medicale + Tipuri publicaţii > Articol în revistã ştiinţificã

Autori: A. Bezerianos, L. Vladutu and S. Papadimitriou

Editorial: IFMBE, IEE Medical and Biological Engineering and Computing, 38(4), p.406-415, 2000.

Rezumat:

Problema maximizarii performantelor in recunoasterea automata a modificarilor segmentului ST-T in detectia ischemiei ramine o problema dificila de „pattern clasification”. Autorii propun o model nou (de tip ierarhizat) de mapa Kohonen, numit NetSOM. Sensitivitatea respectiv predictivitatea recunoasterii modificarilor de segment ST-T au fost de 78% si respectiv 74.1%. The problem of maximizing the performance of ST-T segment automatic recognition for ischaemia detection is a difficult pattern classification problem. The authors propose the network self-organizing map (NetSOM) model as an enhancement to the Kohonen self-organised map (SOM) model. The sensitivity attained was of 78% for an average ischaemic beat predictivity of 74.1%.

Cuvinte cheie: Detectarea automata a ischemiei, mape Kohonen // Automatic Ischemia Detection, Self-organizing maps

URL: http://heart.med.upatras.gr/~liviu