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Neuroevolutionary method of stroke diagnosis

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Abstract

A computer system for classification of stroke types is developed and described. A functioning of the classifying neural network is optimized both by means of learning and in evolutionary way. Investigations of this system demonstrated its effectiveness.

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References

  1. Vereshagin, N.V. and Varakin, Yu. Ya., Stroke Epidemiology in Russia: Results and Epidemiological Aspects of the Problem, Korsakov Journal of Neurology and Psychiatry. Appendix “Stroke”, 2001, no. 1, pp. 34–40 [in Russian].

  2. Rebrova, O.Yu., Application of Methods of Intellectual Data Analysis for Solving Problems of Medical Diagnosis, News Artif. Intell., 2004, no. 3, pp. 76–80 [in Russian].

  3. Red’ko, V.G., Mosalov, O.P., and Prokhorov, D.V., A Model of Evolution and Learning, Neural Networks, 2005, vol. 18, nos. 5–6, pp. 738–745.

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Authors and Affiliations

  1. Center of Optical Neural Technologies, Scientific Research Institute for System Studies, Russian Academy of Sciences, ul. Vavilova 44/2, Moscow, 119333, Russia

    O. P. Mosalov & V. G. Red’ko

  2. Center of Neurology, Russian Academy of Medical Sciences, Volokolamskoe sh. 80, Moscow, 125367, Russia

    O. Yu. Rebrova

Authors
  1. O. P. Mosalov
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  2. O. Yu. Rebrova
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  3. V. G. Red’ko
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The text was submitted by the authors in English.

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Mosalov, O.P., Rebrova, O.Y. & Red’ko, V.G. Neuroevolutionary method of stroke diagnosis. Opt. Mem. Neural Networks 16, 99–103 (2007). https://doi.org/10.3103/S1060992X07020063

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  • DOI: https://doi.org/10.3103/S1060992X07020063

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