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Advances in artificial intelligence and precision nutrition approaches to improve maternal and child health in low resource settings

Author

Listed:
  • Saurabh Mehta

    (Cornell University
    Cornell University
    Cornell Weill Medicine)

  • Samantha L. Huey

    (Cornell University
    Cornell University)

  • Shah Mohammad Fahim

    (Cornell University)

  • Srishti Sinha

    (Cornell University
    Cornell University)

  • Kripa Rajagopalan

    (Cornell University
    Cornell University)

  • Tahmeed Ahmed

    (International Centre for Diarrhoeal Disease Research, Bangladesh (ICDDR, B))

  • Rob Knight

    (University of California San Diego
    University of California San Diego
    University of California San Diego
    University of California San Diego)

  • Julia L. Finkelstein

    (Cornell University
    Cornell University
    Cornell Weill Medicine)

Abstract

Malnutrition continues to be a major threat to health, particularly maternal and child health in low resource settings, resulting in impairments in cognitive function, growth, and development, and metabolic diseases later in life. Nutritional assessment is a cornerstone of any successful nutrition intervention or program whether in the community or at the clinic. Improved computational power and advances in technology may enable precision nutrition-based approaches for maternal and child health, which can complement current methods for nutritional assessment to identify clinical, biochemical, microbiome-related, social, and environmental characteristics to predict responses to nutritional interventions or programs. Precision nutrition has the potential to complement program monitoring, efficacy evaluation, and ultimately to inform design of interventions to improve maternal and child health.

Suggested Citation

  • Saurabh Mehta & Samantha L. Huey & Shah Mohammad Fahim & Srishti Sinha & Kripa Rajagopalan & Tahmeed Ahmed & Rob Knight & Julia L. Finkelstein, 2025. "Advances in artificial intelligence and precision nutrition approaches to improve maternal and child health in low resource settings," Nature Communications, Nature, vol. 16(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-62985-3
    DOI: 10.1038/s41467-025-62985-3
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    References listed on IDEAS

    as
    1. Larsen, Bjorn & Hoddinott, John & Razvi, Saleema, 2023. "Investing in Nutrition: A Global Best Investment Case," Journal of Benefit-Cost Analysis, Cambridge University Press, vol. 14(S1), pages 235-254, June.
    2. Fei Tao & Qinglin Qi, 2019. "Make more digital twins," Nature, Nature, vol. 573(7775), pages 490-491, September.
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