Technology of Personalized Preventive Recommendation Formation Based on Disease Risk Assessment

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. © Springer Nature Switzerland AG 2019.

Authors
Grigoriev O.G.1 , Molodchenkov A.I. 1, 2
Journal
Communications in Computer and Information Science
Publisher
Springer Verlag
Language
English
Pages
298-309
Status
Published
DOI
10.1007/978-3-030-30763-9_25
Volume
1093
Year
2019
Organizations
  • 1 Federal Research Center “Computer Science and Control” of RAS, Vavilova str. 44, kor. 2, Moscow, 119333, Russian Federation
  • 2 RUDN University, Miklukho-Maklaya str. 6, Moscow, 117198, Russian Federation
Keywords
Artificial intelligence; Health optimization; Heterogeneous semantic network; Knowledge base; P4 medicine; Predictive medicine; Risk factors; Risk factors assessment
Date of creation
24.12.2019
Date of change
24.12.2019
Short link
https://repository.rudn.ru/en/records/article/record/55386/
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