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A comparative analysis of the efficiency of probabilistic and possibilistic algorithms for medical diagnostics

  • Theoretical and Mathematical Physics
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Moscow University Physics Bulletin Aims and scope

Abstract

Mathematical methods for pattern recognition and algorithms for the classification of diseases based on them are widely used to solve problems of medical diagnostics [1]. In [2], in order to classify functional disorders of the gastrointestinal tract, an algebraic model of the Kora algorithm was applied. In [3–5] it was shown that to solve many problems of medical diagnostics possibilistic methods for making a medical diagnosis are much more efficient. The present work considers a comparative analysis of probabilistic and possibilistic models of diagnostics, as well as Kora algorithms and the results of their application to solving problems of acute appendicitis diagnostics.

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Authors and Affiliations

  1. Department of Physics, Moscow State University, Moscow, 119991, Russia

    Yu. P. Pyt’ev & V. A. Gazaryan

  2. Department of Applied Mathematics and Information Technologies, Moscow, Russia

    V. A. Gazaryan

  3. Financial University under the Government of the Russian Federation, Moscow, 125993, Russia

    P. B. Rosnitskiy

Authors
  1. Yu. P. Pyt’ev
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  2. V. A. Gazaryan
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  3. P. B. Rosnitskiy
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Corresponding author

Correspondence to V. A. Gazaryan.

Additional information

Original Russian Text © Yu.P. Pyt’ev, V.A. Gazaryan, P.B. Rosnitskiy, 2014, published in Vestnik Moskovskogo Universiteta. Fizika, 2014, No. 3, pp. 8–14.

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Pyt’ev, Y.P., Gazaryan, V.A. & Rosnitskiy, P.B. A comparative analysis of the efficiency of probabilistic and possibilistic algorithms for medical diagnostics. Moscow Univ. Phys. 69, 210–217 (2014). https://doi.org/10.3103/S0027134914030138

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  • DOI: https://doi.org/10.3103/S0027134914030138

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