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Artificial Intelligence in Nutrigenomics: A Critical Review on Functional Food Insights and Personalized Nutrition Pathways

BACKGROUND: This review critically evaluates the applications of artificial intelligence in nutrigenomics, focusing on its role in interpreting functional food-gene interactions, supporting personalized nutrition strategies, and enabling evidence-based dietary interventions for improved health outcomes. METHODS: A systematic literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar to identify studies published between 2010 and 2025 addressing AI applications in nutrigenomics and functional foods. Search terms included "artificial intelligence," "nutrigenomics," "personalized nutrition," and "functional foods." Retrieved records were screened for relevance, methodological rigor, and thematic alignment. Following title, abstract, and full-text screening based on predefined inclusion criteria, 176 articles were assessed in detail, and 142 studies were included in the qualitative synthesis. Data were extracted and synthesized to …

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