FUZZY MATHEMATICAL MODELS FOR PREDICTION AND EARLY DIAGNOSIS OF OCCUPATIONAL DISEASES OF AGRICULTURAL WORKERS IN CONTACT WITH PESTICIDES

The work is devoted to solving the urgent problem of improving the quality of medical care for workers of agriculture in contact with agricultural chemicals. In the course of the research it was shown that the problem of forecasting and early diagnosis of occupational diseases of agricultural workers employed in crop production belongs to the class of poorly formalized problems with fuzzy data structure, which served as the basis for the choice as the basic apparatus of research methodology of synthesis of hybrid fuzzy decision rules. During the synthesis of fuzzy decision rules, it was found that in order to achieve high quality of decision-making, in addition to risk factors associated with pesticides, the level of psychoemotional stress, fatigue and ergonomically defective agricultural machinery, environmental risk factors, individual characteristics of the body, etc. should be used as informative features. As a concrete example, the variant of application of the proposed method and information-analytical model in the synthesis of models of forecasting and diagnosis of diseases of the nervous system from the effects on the human body of nitrates-containing pesticides is described. In the course of mathematical modeling and expert evaluation it was shown that the confidence in the decisions exceeds the value of 0.85. The practical application of the proposed method and models will improve the quality of medical services to employees of agriculture providing an increase in working age and reduce disability.

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