Neural Network Model for Transient Ischemic Attacks Diagnostics


авторы: Vladimir Golovko, Elena Apanel, Alexander Mastykin, Henadzi Vaitsekhovich
In this paper the neural network model for transient ischemic attacks recognition have been addressed. The proposed approach is based on integration of the NPCA neural network and multilayer perceptron. The dataset from clinic have been used for experiments performing. Combining two different neural networks (NPCA and MLP) it is possible to produce efficient performance in terms of detection and recognition transient ischemic attacks. The main advantages of using neural network techniques are the ability to recognize “novel” TIA attack instances, quickness and ability to assist the doctor in making decision.

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