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The Role of Artificial Intelligence in Nutrition Research: A Scoping Review
Open accessAbstract
Artificial intelligence (AI) refers to computer systems doing tasks that usually need human intelligence. AI is constantly changing and is revolutionizing the healthcare field, including nutrition. This review’s purpose is four-fold: (i) to investigate AI’s role in nutrition research; (ii) to identify areas in nutrition using AI; (iii) to understand AI’s future potential impact; (iv) to investigate possible concerns about AI’s use in nutrition research. Eight databases were searched: PubMed, Web of Science, EBSCO, Agricola, Scopus, IEEE Explore, Google Scholar and Cochrane. A total of 1737 articles were retrieved, of which 22 were included in the review. Article screening phases included duplicates elimination, title-abstract selection, full-text review, and quality assessment. The key findings indicated AI’s role in nutrition is at a developmental stage, focusing mainly on dietary assessment and less on malnutrition prediction, lifestyle interventions, and diet-related diseases comprehension. Clinical research is needed to determine AI’s intervention efficacy. The ethics of AI use, a main concern, remains unresolved and needs to be considered for collateral damage prevention to certain populations. The studies’ heterogeneity in this review limited the focus on specific nutritional areas. Future research should prioritize specialized reviews in nutrition and dieting for a deeper understanding of AI’s potential in human nutrition.
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“These tools enhance adherence by tracking biometrics and offering actionable insights to users, making weight management dynamic and adaptive to individual needs [96,97,98,99,100,101,102].”
From Beyond Calories: Individual Metabolic and Hormonal Adaptations Driving Variability in Weight Management—A State-of-the-Art Narrative Review (2024) · cites this paper as [101]
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Metadata
- Authors
- Sosa-Holwerda, A., Park, O.-H., Albracht-Schulte, K., Niraula, S., Thompson, L., & Oldewage-Theron, W.
- Affiliations
- Texas Tech University (US)
- Department of Kinesiology & Sport Management, Texas Tech University, Lubbock, TX 79409, USA
- Corresponding author
- Oldewage-Theron, Wilna
- Venue
- Nutrients
- Publisher
- MDPI AG
- Published
- 2024-06-28
- Volume
- 16
- Issue
- 13
- Pages
- 2066
- ISSN
- 2072-6643 (ISSN-L)
- PMC
- PMC11243505
- OpenAlex
- W4400119754
- Cited by
- 114
- References
- 64
- Citations by year
- 2026: 50 · 2025: 58 · 2024: 6
- FWCI
- 2.60
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nutrients (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- artificial intelligence, nutrition research, dietary assessment, lifestyle intervention, diet-related diseases, AI ethics, artificial intelligence in healthcare
- MeSH terms
- Artificial Intelligence, Humans, Biomedical Research, Nutritional Sciences
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