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An Expert System Prototype for the Early Diagnosis of Pneumonia

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Lecture Notes in Computational Intelligence and Decision Making (ISDMCI 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 77))

Abstract

In this paper, an expert system model prototype based on Bayesian networks is proposed, which makes it possible to provide assistance to a doctor in the early diagnosis of a disease such as “pneumonia”. We designed a static Bayesian network with five key variables to obtain the probabilistic inference of the resulting node that determines the presence or absence of disease in a patient. We consulted with medical experts when selecting and quantifying input and output variables. When constructing a Bayesian model and conducting scenario analysis for a better prognosis of the diagnosis, we consulted with the attending physicians.

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Author information

Authors and Affiliations

  1. Kherson National Technical University, Kherson, Ukraine

    Mariia Voronenko, Luidmyla Lytvynenko & Svitlana Vyshemyrska

  2. National Pirogov Memorial Medical University, Vinnytsya, Ukraine

    Olena Kovalchuk

  3. Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

    Iurii Krak

Authors
  1. Mariia Voronenko
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  2. Olena Kovalchuk
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  3. Luidmyla Lytvynenko
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  4. Svitlana Vyshemyrska
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  5. Iurii Krak
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Corresponding author

Correspondence to Mariia Voronenko .

Editor information

Editors and Affiliations

  1. Department of Physics, Kherson State University, Kherson, Ukraine

    Sergii Babichev

  2. Department of Informatics and Computer Science, Kherson National Technical University, Kherson, Ukraine

    Volodymyr Lytvynenko

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Voronenko, M., Kovalchuk, O., Lytvynenko, L., Vyshemyrska, S., Krak, I. (2022). An Expert System Prototype for the Early Diagnosis of Pneumonia. In: Babichev, S., Lytvynenko, V. (eds) Lecture Notes in Computational Intelligence and Decision Making. ISDMCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 77. Springer, Cham. https://doi.org/10.1007/978-3-030-82014-5_49

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