Mathematical Models for Predicting and Early Diagnosis of Bronchial Asthma in Workers Exposed to Industrial Pesticides

The purpose of reseach to develop models for predicting and early diagnosis of bronchial asthma in production facilities with toxic chemicals in the work area, which provide an acceptable quality of decision-making for preventive medicine.

Methods. Based on the data exploratory analysis as the primary method of investigation was the methodology for the synthesis of a hybrid fuzzy decision rules focused on the synthesis of decision rules under conditions of high uncertainty in the structure of the analyzed data that was modified taking into account peculiarities of the effect of industrial chemicals on human health. The synthesized models take into account the multiplicative and nonlinear effects of interaction of harmful chemicals present in the work area with various structures of the body, which significantly improves the quality of decisions made.

Results. In the course of the research, models were obtained for predicting and early diagnosis of bronchial asthma in workers of electroplating workshops of enterprises in the Kursk region. The resulting fuzzy models took into account production risk factors together with the harmful effects of ergonomics and ecology of electroplating shops and the individual health status of employees. As a result of statistical tests and mathematical modeling, it was found that when predicting confidence in the decision made exceeds the value of 0.85, and confidence in the pre - nosological stage of the disease-0.9.

Conclusion. The obtained models of forecasting and pre-nosological diagnostics of bronchial asthma in the conditions of labor activity of employees of electroplating shops provide the quality indicators of decisions made required for preventive medicine in conditions of insufficient statistics and poorly formalized data structure.

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