Application of fuzzy mathematics models for solving medical diagnostics problems

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Fuzzy set theory and fuzzy logic are a very suitable and applicable framework for developing knowledge-based systems in medicine for tasks such as interpreting medical outcome sets, differentiating syndromes, diagnosing various diseases, choosing optimal treatment tactics, and monitoring patients in real time. fuzzy logic is similar to the system of human thinking and, therefore, can cope with the uncertainties and inaccuracies found by the specialist in the course of working with the patient and making a medical diagnosis. The analysis of modern medical practice and literature sources proves the advantages of using fuzzy data analysis methods. this paper presents an overview of various studies in the field of diseases of the cardiovascular system, cholera, brain tumors, lungs, etc. the successful use of various fuzzy logic systems and classification applications highlights the advantages of using fuzzy logic methods in the fight against diseases that require software for their accurate detection, and concludes that this strategy is applicable to the differential diagnosis and treatment of breast cancer.

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Medical diagnostics, fuzzy logic, breast cancer, consultative and diagnostic systems, machine learning methods

Короткий адрес: https://sciup.org/149139556

IDR: 149139556   |   DOI: 10.15688/mpcm.jvolsu.2021.4.4

Статья научная