FORECASTING OF THE GENERATION OF THE LOWER LIMBS ON THE BASIS OF HYBRID FUZZY MODELS

The work is devoted to the urgent problem of improving the quality of care for patients suffering from critical ischemia of the lower limbs, passing into gangrene, which can result in amputation and even death. In the course of the studies, it was shown that the task of predicting the origin and development of gangrene of the lower limbs belongs to the class of poorly formalizable problems with an indistinct data structure, which served as the basis for choosing as a basic research apparatus the methodology for the synthesis of hybrid fuzzy decision rules. During the synthesis of fuzzy decisive rules, the selection of informative signs obtained during surveys and examinations, instrumental and laboratory methods of investigation was justified. As the basic elements of fuzzy decision rules, the functions of belonging to the class of high risk of gangrene development are obtained, which are aggregated into an unclear rule of confidence assessment that the patient will develop gangrene of the lower limbs. On a scale of confidence in the development of gangrene, experts determined the secondary functions of belonging to such predictable classes of patient conditions as: I - low confidence in gangrene development; II - moderate confidence in the development of gangrene; III - high confidence in the development of gangrene; IV - very high confidence in the development of gangrene. The decision to classify is taken based on the maximum value of prognostic membership functions. The performed mathematical modeling and expert evaluation of the fuzzy models obtained showed that their predictive confidence is at least 0.9. The same quality of forecasting was confirmed during statistical tests on control samples of 100 persons per class for such indicators as diagnostic specificity, sensitivity and efficiency, as well as prognostic significance of positive and negative results. The results obtained make it possible to recommend the proposed mathematical models for use in the practice of cardiovascular surgeons and angiologists.

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