employee
Omsk, Omsk, Russian Federation
employee
Omsk, Omsk, Russian Federation
employee
Moskva, Moscow, Russian Federation
Background. At the present stage of development of scientific knowledge, to know the etiology and pathogenesis of dental diseases is impossible without a systematic approach to this problem. Currently, the problem of forecasting and the formation of “risk groups” at the stages of disease development and determining the boundary values of background indicators of diagnostic criteria in order to prevent the development of pathology and take preventive measures is relevant. In order to process the information received, elements of applied mathematics are increasingly being used, namely cluster and factor analyzes for processing the data from physiological parameters to the onset of pathology. These methods of applied mathematics are a component of modern computer software packages and are used for mathematical modeling of the clinical situation. The goal ― is to create and test a model for predicting dental caries in children in the pediatric dentistry clinic with the help of a systematic approach using elements of applied mathematics. Methods. 1158 caries-resistant children of pre-school and school age were examined for the study of dental status and the formation of a regional data bank. Results. The applied system approach with the use of elements of applied mathematics allowed introducing into practical public health computer processing of data of clinical and laboratory diagnostics of the dental status of caries resistant children of preschool and school age in order to predict the risk of developing a carious process in each individual. Findings. Predicting the risk of a carious process will increase the effectiveness of primary preventive measures, save public funds allocated in the amount of compulsory health insurance to provide dental care for children in the region, maintains caries resistance in each individual and, subsequently, will reduce the incidence of caries among the children's population at populations.
dental caries, risk factors, disease prognosis, prevention
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