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Cited by 125Artificial Intelligence in Healthcare and EducationNutrition, Genetics, and DiseaseArtificial Intelligence Applications

The DOI matches its Crossref record; 63 of the 64 references it cites were found in a registry or an index.

The Role of Artificial Intelligence in Nutrition Research: A Scoping Review

Open access
Sosa-Holwerda, Andrea, Park, Oak-Hee, Albracht-Schulte, Kembra, Niraula, Surya, Thompson, Leslie, Oldewage-Theron, Wilna·2024·Nutrients
DOI 10.3390/nu16132066PMC PMC11243505
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Abstract

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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Research works printed but not linked: 2

  1. Nunes-Galbes, N.M. (2022). Systematic Reviews in Nutrition Using Artificial Intelligence Tools: A Brief Review, Faculty of Public Health, University of São Paulo.
  2. Narkhede, 2018, Understanding auc-roc curve, Towards Data Sci., 26, 220

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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
ORCID
Venue
Nutrients
Publisher
MDPI AG
Published
2024-06-28
Volume
16
Issue
13
Pages
2066
ISSN
2072-6643 (ISSN-L)
DOI
10.3390/nu16132066
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
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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