Fuzzy logical conclusions and conclusions in expert systems of medical diagnostics
DOI:
https://doi.org/10.20535/SRIT.2308-8893.2021.3.05Keywords:
cluster analysis, multidimensional membership functions, centroids of fuzzy-sets of objects and clusters, centers of gravity and mid-sections of fuzzy sets, optimality criteria and clustering algorithmsAbstract
The main problems in making a correct diagnosis are: subjectivity and insufficient qualifications of the doctor, difficulties in correctly assessing the patient’s complaints, signs and symptoms of the disease observed in the patient, as well as individual manifestations of the symptoms of the disease. In publications on the use of expert systems for medical diagnostics using fuzzy logic, the main attention was paid to the medical features of the problem. In this work, for the first time, general methodological aspects of building such systems, creating databases, representing by fuzzy sets of real numbers, digital scales, linguistic and Boolean data of symptom values are formulated. The types of membership functions that are advisable to use to represent the symptoms of diseases are proposed. In fuzzy-logical conclusions, not only the values of the characteristic functions of the logical terms of individual symptoms, but also complex arithmetic functions of their values are used.
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