The Personalized Approach to the Processing and Analysis of Patients' Medical Data

The application of machine learning technology and Big data to solve the problem of personalized approach in the tasks of making medical decisions and predicting states will allow to study random mechanisms of modeling and forecasting of treatment stages taking into account individual patient's characteristics, analysis of the medicaments and their key characteristics. We use this information to develop innovative approaches to risk forecasting, modeling therapies, and improving the quality of medical care by personalizing treatment schemes of patients. And it will allow you to effectively optimize data processing even when new information revenues come from different sources. The authors proposed the development of a System for the medical decisions support for the personalized data consolidation of the patient, which were receiving from the heterogeneous sources that are related healthcare. The conceptual scheme of the system was proposed and new approaches to consolidation and analysis of patient's data and forecasting of its states are offered. The use of various processing technologies for the Big data obtained will allow the study of random mechanisms for modeling and predicting treatment stages, taking into account individual patient's characteristics, analysis of the medicaments and their key characteristics. These will help develop innovative approaches to improve the risk stratification methodology, improve the quality of medical care by personalizing treatment schemes for patients.

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