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    Online Resource
    Online Resource
    Annual Reviews ; 2023
    In:  Annual Review of Nutrition Vol. 43, No. 1 ( 2023-08-21), p. 225-250
    In: Annual Review of Nutrition, Annual Reviews, Vol. 43, No. 1 ( 2023-08-21), p. 225-250
    Abstract: Modernization of society from a rural, hunter-gatherer setting into an urban and industrial habitat, with the associated dietary changes, has led to an increased prevalence of cardiometabolic and additional noncommunicable diseases, such as cancer, inflammatory bowel disease, and neurodegenerative and autoimmune disorders. However, while dietary sciences have been rapidly evolving to meet these challenges, validation and translation of experimental results into clinical practice remain limited for multiple reasons, including inherent ethnic, gender, and cultural interindividual variability, among other methodological, dietary reporting–related, and analytical issues. Recently, large clinical cohorts with artificial intelligence analytics have introduced new precision and personalized nutrition concepts that enable one to successfully bridge these gaps in a real-life setting. In this review, we highlight selected examples of case studies at the intersection between diet–disease research and artificial intelligence. We discuss their potential and challenges and offer an outlook toward the transformation of dietary sciences into individualized clinical translation.
    Type of Medium: Online Resource
    ISSN: 0199-9885 , 1545-4312
    URL: Issue
    Language: English
    Publisher: Annual Reviews
    Publication Date: 2023
    detail.hit.zdb_id: 1481486-9
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