The dental implantation has recently become one of the most popular methods of treating complete or partial lack of teeth. Prosthetics on dental implants is a rehabilitation method for patients with dental defects, which allows solving the issues of professional, social, psychological, physiological, and aesthetic nature. Taking into account the existing clinical features of the somatic and dental condition of a patient, the dentist chooses an optimal method of dental implantation for each case. The complexity of medical decision is conditioned by the high level of responsibility that is why decisions are made not by one criterion, but by the set of many criteria considered simultaneously. The purpose of the work was to develop a decision-making support system for a dentist regarding the choice of dental implantation method. Material and methods. For the development of a decision-making support system, we analyzed the results of dental implantation of 90 patients, who had been set 180 implants. Preoperative laboratory studies of patients included clinical blood and urine tests, bacteriological sowings from the oral cavity, and also biochemical studies (determination of the level of sugar, calcium and phosphorus in the blood). We determined the absorption coefficient of the jaw tissue based on the results of X-ray studies. Using the Osstell ISQ apparatus, we assessed an implantation stability quality intraoperatively after its installation. The depth of the ascetic furrow was measured by the probing method; the index of gum bleeding was determined taking into account the number of the tooth which was implanted. Patients underwent the direct dental implantation with immediate or postponed loading, as well as standard two-stage implantation according to their indications. Results and discussion. We used fuzzy logic and subtractive clustering (by mountain method) to develop the results of the dental implantation prediction models. This clustering method allows the patients to be divided into groups with the same mechanisms of the studied indices influence on the result of dental implantation. To construct a prediction model for the dental implantation result, the Sugeno system of fuzzy inference was used. According to the data of patients who were conducted dental implantation by different methods, three fuzzy models were obtained, each consisting of two fuzzy logic equations, two functions of fuzzy rule belonging to the corresponding input variable, and two linear functions in the derivation of fuzzy rules for forecasting dental implantation results. The prediction of the dental implantation results with the general accuracy of prediction at 94.5% was performed according to the following intraoperative indicators: the ascetic furrow depth and the implant stability quality coefficient. Conclusions. Using the developed decision-making support system and the set of models for assessing intraoperative indexes of patients can help in prediction of the success of dental implantation conducted by different methods. These factors allow choosing the optimal implantation method in each case or adjusting the rehabilitation plan of the patient in case of obtaining an unfavorable prognosis.
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