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Neural network model for transient ischemic attacks diagnostics

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Abstract

In this paper the neural network model for transient ischemic attacks (TIA) recognition is described. The proposed approach is based on integration of nonlinear principal component analysis (NPCA) neural network and multilayer perceptron (MLP). The data set from clinic was used for experiments performing. At combining the two different neural networks (NPCA and MLP) it is possible to produce efficient performance in terms of transient ischemic attacks detection and recognition. The main advantages of using the neural network techniques are the ability to recognize “novel” TIA instances, quickness and ability to assist a doctor in making decision.

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Author information

Authors and Affiliations

  1. Brest State Technical University, Brest, Belarus

    V. Golovko & Henadzi Vaitsekhovich

  2. Scientific and Clinical Center of Neurology and Neurosurgery, Minsk, Belarus

    E. Apanel

  3. Belarusian Medical Academy of Post-Graduate Education, Minsk, Belarus

    A. Mastykin

Authors
  1. V. Golovko
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  2. Henadzi Vaitsekhovich
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  3. E. Apanel
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  4. A. Mastykin
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Corresponding author

Correspondence to V. Golovko.

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The article was translated by the author.

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Golovko, V., Vaitsekhovich, H., Apanel, E. et al. Neural network model for transient ischemic attacks diagnostics. Opt. Mem. Neural Networks 21, 166–176 (2012). https://doi.org/10.3103/S1060992X12030095

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  • DOI: https://doi.org/10.3103/S1060992X12030095

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