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.

Авторы
Grigoriev O.G.1 , Molodchenkov A.I. 1, 2
Издательство
Springer Verlag
Язык
Английский
Страницы
298-309
Статус
Опубликовано
Том
1093
Год
2019
Организации
  • 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
Ключевые слова
Artificial intelligence; Health optimization; Heterogeneous semantic network; Knowledge base; P4 medicine; Predictive medicine; Risk factors; Risk factors assessment
Дата создания
24.12.2019
Дата изменения
24.12.2019
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/55386/
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