Analysis of the literature and the results of own stud ies lead to the conclusion that a significant number of problems of predictive medicine, early and differential diagnosis, are characterized by high complexity of description formalization of classes of health conditions. In problems of prediction and early diagnosis, various classes greatly overlap in the space of informative features [3, 5, 7 9]. In addition, for a number of socially impor tant problems building of predictive and diagnostic math ematical models is characterized by incomplete and vague representation of the original data. In such circum stances, some researchers recommend using fuzzy deci sion making [3,7,8,11,12,15].One of the main problems of practical application of this mathematical apparatus is the difficulty of selecting the shape and parameters of elements of fuzzy decision rules and methods of their aggregation into systems of fuzzy decision rules. Most of these problems can be solved by the application of groups of fuzzy decision rules, with training performed using data of exploratory analysis.The practice of solving problems of medical predic tion and diagnostics showed that under conditions of poor formalization with insufficient statistics and choice of the type of decision rules, unified in groups, it is most appropriate to use Wald sequential analysis, dialog sys tems of pattern recognition, and fuzzy decision making in its applications in solving classification problems [3, 4, 46 0006 3398/15/4901 0046

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Many theories of reflexology use ancient concepts which do not coincide with the modern medical terminology of anatomy, physiology and biophysics. This substantially reduces the trust of physicians in reflexology methods. During this research, several mathematical models for the interaction of the internal and biological active points of meridian structures have been proposed. The analysis of these models allows the specification of a list of gastric diseases for which reflex diagnostics and reflex therapy methods are most effective and also allows increasing the effectiveness of these procedures. It is shown that good results for the prediction and early diagnosis of diseases from the reaction energy of biologically active points (acupuncture points) are obtained using fuzzy logic decision making.

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