Development of mathematical methods for diagnosing kidney diseases using fuzzy set tools
Myrzakerimova A. Kolesnikova K.
July 2024Institute of Advanced Engineering and Science
Indonesian Journal of Electrical Engineering and Computer Science
2024#35Issue 1405 - 417 pp.
An approach based on fuzzy set theory is presented in the scientific article to enhance the efficiency of diagnosing kidney diseases by decreasing the time required for making medical decisions. The suggested approach employs fuzzy models and algorithms that consider the uncertainty and variability of clinical data to optimize the assessment of the functional state of the kidneys, taking into account various risk factors and individual characteristics of patients. The paper suggests a technique to develop a system of fuzzy decision rules. This technique combines E. Shortliff’s iterative rules with functions from the studied classes of kidney diseases. Mathematical modeling and experimental studies have indicated relatively high effectiveness in classifying different forms of kidney diseases. The results can be used to formulate intelligent decision support systems in clinical practice and improve diagnostic and monitoring processes. Moreover, the findings may aid in shaping more targeted and effective health policies at the national and regional levels, enhancing access to healthcare, and promoting the population’s overall health.
Dataset of pyelonephritis Decision support system Diagnosing kidney diseases Fuzzy logic method Morbidity analysis
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Department of Information Systems, Faculty of Business, Media and Management, International IT University, Almaty, Kazakhstan
Department of Information Systems
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