Design of Information Technology Classification Based on Medical Data

Decision-making processes associated with assigning a person to a risk group for diseases are accompanied by the need to analyze large volumes of medical and social data. At the same time, a qualified doctor must operate both the patient’s personal data and the relevant treatment protocols and instructions. Early prediction of the risks of disease occurrence allows medical workers to plan, develop a system of preventive measures, and the like. Therefore, the object of research is to support and provide information and analytical support for decision-making processes for early predicting the risks of diseases in individuals based on medical data. Such support is necessary to analyze the experience of a medical worker, which is recorded in the form of statistical data. One of the most problematic areas at the design and implementation stage of relevant information technology is the collection and analysis of statistical data on the problem under study.The study was carried out in accordance with the systema tic approach methodology. All stages of the design of information technology for forecasting based on medical data correspond to the stages of a systematic approach: systematization, formalization, goal orientation. The developed technology is based on the classification method based on Wald’s sequential analysis.The research resulted in:– built a mathematical model of the problem of predicting the risks of disease occurrence as a classification problem;– a functional diagram of an information and analytical system has been developed to solve the classification problem based on medical data. The analytical core of the information and analytical system is formed by algorithms for statistical data processing, as well as a classification method based on Wald’s sequential analysis;– experimental verification of the developed technology for the task of predicting the occurrence of dentoalveolar anomalies in children has been performed. Based on the available statistical data, a differential prognostic table was constructed. All calculations are performed. The examples demonstrate the effectiveness of the developed technology.The developed information technology can be used by medical workers in the process of early forecasting of the risks of disease