Digital Nutrition Powered by Artificial Intelligence: Personalization, Prediction and Prevention
A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition and Public Health".
Deadline for manuscript submissions: 15 August 2026
Special Issue Editor
Interests: health informatics; digital health; mHealth; eHealth; nutrition; health diseases
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Rapid advances in artificial intelligence are reshaping the foundations of nutrition science, enabling a shift from generalized dietary guidance toward highly personalized, predictive, and preventive nutrition strategies. The emergence of digital nutrition—the integration of data-driven models, computational intelligence, and real-world nutritional signals—offers unprecedented opportunities to understand individual variability, anticipate health risks, and design targeted nutritional interventions across the lifespan.
This Special Issue, “Digital Nutrition Powered by Artificial Intelligence: Personalization, Prediction and Prevention,” aims to showcase cutting-edge research and critical perspectives on how artificial intelligence and related computational approaches are transforming nutrition assessment, monitoring, and intervention. By leveraging multimodal data sources—including dietary intake, metabolic markers, behavioral patterns, and environmental factors—AI-driven systems can support precision nutrition, early risk prediction, and preventive strategies for nutrition-related conditions and chronic diseases.
We invite original research articles, comprehensive and systematic reviews, methodological papers, and proof-of-concept studies that explore the development, validation, and application of AI-enabled digital nutrition approaches. Contributions addressing translational impact, scalability, ethical considerations, and future directions toward predictive and preventive nutrition frameworks are particularly encouraged.
This Special Issue seeks to advance interdisciplinary dialog and provide a forward-looking platform that bridges current innovations with the evolving vision of intelligent, personalized nutrition systems.
Dr. Sasan Adibi
Guest Editor
Manuscript Submission Information
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Keywords
- digital nutrition
- non-invasive diagnostics
- nutritional biomarkers
- AI and machine learning in nutrition
- digital twins in health monitoring
- spectroscopic and imaging technologies
- wearable devices and biosensors
- point-of-care diagnostic tools
- nutritional deficiency detection
- digital health integration
- inflammation and chronic disease monitoring
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