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The paper describes the optimization of the prediction of disease at the primary health care level with a complex phased application of information techniques. The approach is based on analysis of the average values of indicators, correlation coefficients, using multi-parameter neural network clustering, ROC-analysis and decision tree.The data of 63 patients with arterial hypertension obtained at teaching and practical centers of primary health care were used for the analysis. It has beendoi:10.11603/mie.1996-1960.2016.3.6749 fatcat:ytx6hkfogzdlzemqaea6xypdiy