Artificial Intelligence in Clinical Nutrition: Bridging Data Analytics and Nutritional Care.

Journal: Current nutrition reports
Published Date: Jul 3, 2025

Abstract

PURPOSE OF REVIEW: This review explores how artificial intelligence can help advance clinical nutrition and address nutrition education and practice challenges. It highlights the role of AI, mainly through advanced clinical decision-making using generative AI, in supporting clinicians as they develop personalized nutrition interventions for individual patients. Furthermore, the review discusses how AI technologies are helping to close the knowledge gap in nutrition and delivering real-time, evidence-based insights to healthcare professionals.

Authors

  • Jithinraj Edakkanambeth Varayil
    Department of Family Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA. edakkanambethvarayil.jithinraj@mayo.edu.
  • Suzette J Bielinski
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, 55905, USA. bielinski.suzette@mayo.edu.
  • Manpreet S Mundi
    Mayo Clinic, Rochester, MN, USA.
  • Sara L Bonnes
    Division of General Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
  • Bradley R Salonen
    Division of General Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
  • Ryan T Hurt
    Mayo Clinic, Rochester, MN, USA.

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