Technology of Personalized Preventive Recommendation Formation Based on Disease Risk Assessment

Abstract

The paper describes the technology of forming a list of personalized preventive recommendations. The technology consists of the following main components: human health state, data acquisition module, database, knowledge base, and solver with output explanation. In the version presented, this technology allows one to assess the risks of stroke, myocardial infarction and depression, contains more than two hundred risk factors for these diseases and more than twenty preventive recommendations. Training for this version was based on automated analysis of a large number of publications and expert knowledge.