AI-driven personalized nutrition: Integrating omics, ethics, and digital health

verfasst von

Celin Mundt, Büşra Yusufoğlu, Daniel Kudenko, Kerem Mertoğlu, Tuba Esatbeyoglu

Abstract

Personalized nutrition (PN) aims to prevent and manage chronic diseases by providing individualized dietary guidance based on genetic, metabolic, and lifestyle data. Artificial intelligence (AI) has become a key enabler in PN by analyzing large-scale, multiomics datasets in obesity, diabetes, cardiovascular, and gastrointestinal disorders, where digital twins and health knowledge graphs support personalized interventions. Current findings demonstrate that AI models can guide microbiome-based dietary interventions, and support obesity management, thereby extending the scope of conventional nutritional strategies as supported by deepened bibliometric analyses. This study highlights the global increase in AI-based PN studies, accelerated by digital health demands and the COVID-19 pandemic, and the expansion of traditional nutrition strategies through machine learning approaches with the integration of microbiome-based models and omics. However, challenges such as algorithmic bias, limited generalizability, and data privacy remain. To overcome these issues, diverse datasets, explainable AI approaches, and standardized multicenter validation protocols are proposed. These steps are critical for transforming AI-supported PN from a conceptual potential into a fair, reliable, and clinically applicable structure. The growing consensus in the literature highlights that AI can support individual and societal health goals by transforming nutrition science through predictive, adaptive, and ethically based approaches.

Organisationseinheit(en)

Forschungszentrum L3S
Institut für Lebensmittelwissenschaft und Humanernährung
Institute of Food and One Health
Molekulare Lebensmittelchemie und -entwicklung

Externe Organisation(en)

Technische Universität Istanbul
Usak University

Typ

Übersichtsarbeit

Journal

Molecular Nutrition and Food Research

Band

69

ISSN

1613-4125

Publikationsdatum

12.12.2025

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Biotechnologie, Lebensmittelwissenschaften

Ziele für nachhaltige Entwicklung

SDG 3 – Gute Gesundheit und Wohlergehen

Elektronische Version(en)

https://doi.org/10.1002/mnfr.70293 (Zugang: Offen)