Improved algorithms for calculating evaluations in processing medical data

Authors

  • Nishanov AK Department of Information Technology Software, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Uzbekistan
  • Djurayev GP Independent researcher of the Scientific Innovation Center, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Uzbekistan
  • Khasanova MA Assistant of the Department of Hospital Therapy of Faculty No. 2, Tashkent Medical Academy, Uzbekistan

Keywords:

pattern recognition, remoteness and proximity functions, estimation algorithms, classification, informative features

Abstract

The paper examines the issues of diagnosis and treatment of cardiovascular diseases, commonly encountered in diagnostic decision-making, when medical data are processed. The issues of classification of heart diseases and detection of informative signs are solved on the basis of estimation algorithms. In addition, the appropriate software was developed. The main goal of the research is to solve such issues as constructing inter-object remoteness in a complex of informative features that distinguish objects of diagnostic classes, select a complex of signs that characterize mutual differences of objects, and also identify the value of the proximity function when diagnosing an unknown object [1-5]. The level of significance or representation of the set belonging to the j-object ofХр-class, which are the main stages of the algorithms for calculating its assessment relative to the class [1-5], was revealed. An algorithm for diagnosing an unknown object in the space of informative features was proposed. The suggested theoretical ideas were confirmed in practice. In addition, the decision rules in this space and their software were developed [4-5].

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Published

2024-02-26

How to Cite

Nishanov, A. K., Djurayev, G. P., & Khasanova, M. A. (2024). Improved algorithms for calculating evaluations in processing medical data. COMPUSOFT: An International Journal of Advanced Computer Technology, 8(06), 3158–3165. Retrieved from https://ijact.in/index.php/j/article/view/496

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Section

Original Research Article

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