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The Important Role of Artificial Intelligence in Nutrition Assessment and Healthy Eating

A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition Methodology & Assessment".

Deadline for manuscript submissions: closed (15 November 2025) | Viewed by 1870

Special Issue Editor


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Guest Editor
Division of Hospital Internal Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
Interests: nutrition; cardiology; public health; population heatlh; artificial intelligence; equity; ethics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) is emerging as a powerful but still nascent tool in nutrition and healthy eating assessments as a cost-efficient adjunct for more equitable and effective individual healthcare, population health, and public health. Toward such health improvements, there are promising use cases suggesting the efficacy of AI, especially in deep learning, machine learning, wearable devices, and chatbots, to improve dietary tracking and guide more personalized nutrition, especially as part of chronic disease management in cardiovascular disease, hypertension, diabetes, and obesity. Yet there are significant research gaps in this field on the explosive rise in next-generation AI agents, platforms, infrastructure, computer vision, and the scaling of promising interventions. Even less understood is the ethical guidance, cost-effectiveness, healthy equities, environmental sustainability, and health policy translation of such AI applications for nutrition. This Special Issue welcomes the submission of original research and review papers to fill these knowledge gaps.

Dr. Dominique Monlezun
Guest Editor

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Keywords

  • artificial intelligence
  • precision nutrition
  • nutrition
  • malnutrition
  • obesity
  • food security

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Published Papers (1 paper)

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Review

18 pages, 679 KB  
Review
The Responsible Health AI Readiness and Maturity Index (RHAMI): Applications for a Global Narrative Review of Leading AI Use Cases in Public Health Nutrition
by Dominique J. Monlezun, Gary Marshall, Lillian Omutoko, Patience Oduor, Donald Kokonya, John Rayel, Claudia Sotomayor, Oleg Sinyavskiy, Timothy Aksamit, Keir MacKay, David Grindem, Dhairya Jarsania, Tarek Souaid, Alberto Garcia, Colleen Gallagher, Cezar Iliescu, Sagar B. Dugani, Maria Ines Girault, María Elizabeth De Los Ríos Uriarte and Nandan Anavekar
Nutrients 2026, 18(1), 38; https://doi.org/10.3390/nu18010038 - 22 Dec 2025
Viewed by 1442
Abstract
Poor diet is the leading preventable risk factor for death worldwide, associated with over 10 million premature deaths and USD 8 trillion related costs every year. Artificial intelligence or AI is rapidly emerging as the most historically disruptive, innovatively dynamic, rapidly scaled, cost-efficient, [...] Read more.
Poor diet is the leading preventable risk factor for death worldwide, associated with over 10 million premature deaths and USD 8 trillion related costs every year. Artificial intelligence or AI is rapidly emerging as the most historically disruptive, innovatively dynamic, rapidly scaled, cost-efficient, and economically productive technology (which is increasingly providing transformative countermeasures to these negative health trends, especially in low- and middle-income countries (LMICs) and underserved communities which bear the greatest burden from them). Yet widespread confusion persists among healthcare systems and policymakers on how to best identify, integrate, and evolve the safe, trusted, effective, affordable, and equitable AI solutions that are right for their communities, especially in public health nutrition. We therefore provide here the first known global, comprehensive, and actionable narrative review of the state of the art of AI-accelerated nutrition assessment and healthy eating for healthcare systems, generated by the first automated end-to-end empirical index for responsible health AI readiness and maturity: the Responsible Health AI readiness and Maturity Index (RHAMI). The index is built and the analysis and review conducted by a multi-national team spanning the Global North and South, consisting of front-line clinicians, ethicists, engineers, executives, administrators, public health practitioners, and policymakers. RHAMI analysis identified the top-performing healthcare systems and their nutrition AI, along with leading use cases including multimodal edge AI nutrition assessments as ambient intelligence, the strategic scaling of practical embedded precision nutrition platforms, and sovereign swarm agentic AI social networks for sustainable healthy diets. This index-based review is meant to facilitate standardized, continuous, automated, and real-time multi-disciplinary and multi-dimensional strategic planning, implementation, and optimization of AI capabilities and functionalities worldwide, aligned with healthcare systems’ strategic objectives, practical constraints, and local cultural values. The ultimate strategic objectives of the RHAMI’s application for AI-accelerated public health nutrition are to improve population health, financial efficiency, and societal equity through the global cooperation of the public and private sectors stretching across the Global North and South. Full article
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