Ischemia Detection with a Self-Organizing Map Supplemented by Supervised Learning
The problem of maximizing the performance of the detection of ischemia episodes is a difficult pattern classification problem. The state space for this problem is consisted of regions that lie near class separation boundaries and require the construction of complex discriminants while for the rest regions the classification task is significantly simpler. The motivation for developing the Network Self-Organizing Map (NetSOM) model is to exploit this
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