Implications of Artificial Intelligence in Clinical Nutrition and Non-Communicable Chronic Related Diseases of Obesity for Patients and Health Professionals
A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Clinical Nutrition".
Deadline for manuscript submissions: 20 November 2025 | Viewed by 155
Special Issue Editor
2. Instituto de Endocrinología y Nutrición (IENVA), Universidad de Valladolid, Av. Ramón y Cajal, 3, 47003 Valladolid, Spain
Interests: obesity; nutrigenetics; enteral nutrition; malnutrition related to the disease
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid evolution of artificial intelligence (AI) is reshaping numerous scientific disciplines, and clinical nutrition is experiencing a significant transformation as a result. This Special Issue of Nutrients is dedicated to exploring how AI-driven technologies are revolutionizing the field by addressing critical challenges, refining research methodologies, and enabling the development of highly personalized and precise nutritional interventions and new potential diagnostic tools. By leveraging AI, researchers can uncover complex relationships between diet, obesity, non-communicable chronic diseases related to obesity, and malnutrition related to disease. These new potentialities will allow for new diagnostic approaches with images and various biological signals in this type of disease, approaches to the analysis of large databases with the discovery of new diagnostic or prognostic algorithms, and even the design of new educational strategies for health professionals and new methodologies in clinical and basic research, as well as translational research.
This new Special Issue will feature pioneering studies and innovative applications of AI in clinical nutrition. Topics of interest include the use of general artificial intelligence in clinical nutrition, virtual assistants, or chat bots for training health professionals, metaverse tools, deep learning and machine learning techniques in nutritional diseases databases, medical image segmentation tools for nutritional diagnosis, and new explanatory artificial intelligences and their uses in clinical nutrition, as well as new educational and research strategies using cutting-edge tools in artificial intelligence.
As Guest Editor, I warmly encourage researchers, professors, and professionals in the field of clinical nutrition to submit original studies, meta-analyses, and comprehensive reviews that explore contemporary challenges, introduce ground-breaking AI methodologies, or demonstrate the real-world applications of AI in this broad field of clinical nutrition and diseases. Through this collective effort, we aim to deepen our knowledge of AI’s transformative potential in clinical nutrition and to inspire future innovations, with the aim to improve the health of our patients.
Dr. Daniel-Antonio de Luis Roman
Guest Editor
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nutrients is an international peer-reviewed open access semimonthly journal published by MDPI.
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Keywords
- artificial intelligence
- chat-bots
- clinical nutrition
- deep and machine learning
- education
- explainable artificial intelligence
- generative artificial intelligence
- image analysis-based AI
- malnutrition
- non-communicable chronic diseases related to obesity
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