[Automated decision making support system for urologists on the prediction and the prevention of stone formation in urolithiasis].

This article describes a decision making support system for urologists on the prediction and management of preventive interventions for urolithiasis using fuzzy logic decision-making device. Dictionary of informative signs and alphabet of classes are formed. The formulas for calculating the membership functions according to the known features are developed; these formulas allow to calculate the certainty factors for pertaining of inspected object to the desired class by means of iterative rules of rule of logical inference. Based on comparison of the values obtained with the threshold certainty factors, dephasification of conclusion is produced. In accordance with the obtained decision rules, control algorithm for the prevention measures in urolithiasis is developed. To test the effectiveness of "operation" of the synthesized decision rules, the certainty factors were calculated or 200 patients with urolithiasis, which were divided into two groups according to the results of observation during the year depending on the presence of recurrence. The analysis of the intersection of histograms of distribution of coefficient values showed high diagnostic efficiency (0.94) of synthesized decision rules.

[Automatic decision support system in prognostication, diagnosis, treatment and prophylaxis of chronic prostatitis].

A great variety of subjective and objective disorders related with chronic prostatitis make difficulties in its diagnosis. The proposed principle of chronic prostatitis classification identifies 33 clinically significant variants of diagnosis by combination of classification grades. The system of fuzzy decisive rules for prediction and differential diagnosis of chronic prostatitis supports decision on the level 0.9 and higher. Use of energetic characteristics of diagnostically significant biologically active points raises quality of prognosis of the onset and exacerbation of chronic prostatitis and helps to select optimal schemes of acpuncture. Application of decision support systems for urological decision on prognosis, diagnosis, prevention and treatment of chronic prostatitis improves quality of medical aid and adequate management of patients with chronic prostatitis.