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    COVID and nutrition: A machine learning perspective

    , Article Informatics in Medicine Unlocked ; Volume 28 , 2022 ; 23529148 (ISSN) Jafari, N ; Besharati, M. R ; Izadi, M ; Talebpour, A ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    A self-report questionnaire survey was conducted online to collect big data from over 16000 Iranian families (who were the residents of 1000 urban and rural areas of Iran). The resulting data storage contained over 1 M records of data and over 1G records of automatically inferred information. Based on this data storage, a series of machine learning experiments was conducted to investigate the relationship between nutrition and the risk of contracting COVID-19. With highly accurate scores, the findings strongly suggest that foods and water sources containing certain natural bioactive and phytochemical agents may help to reduce the risk of apparent COVID-19 infection. © 2022 The Author(s)  
Total 541 records