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Nutrients
Special Issues
Use of Artificial Intelligence to Fight Malnutrition and Food Insecurity
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Use of Artificial Intelligence to Fight Malnutrition and Food Insecurity

A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition and Public Health".

Deadline for manuscript submissions: 20 December 2025 | Viewed by 625

Special Issue Editor

Dr. Ruopeng An

E-Mail Website
Guest Editor
Constance and Martin Silver Center on Data Science and Social Equity, New York University Silver School of Social Work, New York, NY 10003, USA
Interests: dietary behavior; public health nutrition; physical activity; obesity; diabetes; cognitive health; food environment; built environment; cost-benefit analysis; cost-effectiveness analysis; microsimulation; machine learning; policy analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to explore the transformative potential of artificial intelligence (AI) in reducing malnutrition and food insecurity. AI-driven solutions are already making significant impacts, such as using big data analytics for comprehensive food insecurity assessments, AI-powered nutritional interventions tailored to the needs of vulnerable populations, and AI-based early warning systems for predicting and mitigating food shortages. Additionally, AI is crucial in the policy planning and implementation of food security, in optimizing food assistance programs, and in enhancing food security in post-disaster scenarios. By improving the efficiency of food distribution networks and the nutritional quality of food aid, AI technologies are driving sustainable and equitable access to nutritious food. This Special Issue will showcase the latest advancements and foster collaborative efforts to combat malnutrition and food insecurity through interdisciplinary research and real-world practices.

Dr. Ruopeng An
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • machine learning
  • deep learning
  • artificial neural network
  • data science
  • nutrition
  • diet
  • population health
  • public health
  • malnutrition

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Published Papers (1 paper)

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13 pages, 576 KiB  
Systematic Review
Artificial Intelligence in Food Bank and Pantry Services: A Systematic Review
by Yuanyuan Yang, Ruopeng An, Cao Fang and Dan Ferris
Nutrients 2025, 17(9), 1461; https://doi.org/10.3390/nu17091461 - 26 Apr 2025
Viewed by 206
Abstract
Background/Objectives: Food banks and pantries play a critical role in improving food security through allocating essential resources to households that lack consistent access to sufficient and nutritious food. However, these organizations encounter significant operational challenges, including variability in food donations, volunteer shortages, and [...] Read more.
Background/Objectives: Food banks and pantries play a critical role in improving food security through allocating essential resources to households that lack consistent access to sufficient and nutritious food. However, these organizations encounter significant operational challenges, including variability in food donations, volunteer shortages, and difficulties in matching supply with demand. Artificial intelligence (AI) has become increasingly prevalent in various sectors of the food industry and related services, highlighting its potential applicability in addressing these operational complexities. Methods: This study systematically reviewed empirical evidence on AI applications in food banks and pantry services published before 15 April 2025. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A comprehensive keyword and reference search was conducted in 11 electronic bibliographic databases: PubMed, Web of Science, Scopus, MEDLINE, APA PsycArticles, APA PsycInfo, CINAHL Plus, EconLit with Full Text, Applied Science & Technology Full Text (H.W. Wilson), Family & Society Studies Worldwide, and SocINDEX. Results: We identified five peer-reviewed papers published from 2015 to 2024, four of which utilized structured data machine learning algorithms, including neural networks, K-means clustering, random forests, and Bayesian additive regression trees. The remaining study employed text-based topic modeling to analyze food bank and pantry services. Of the five papers, three focused on the food donation process, and two examined food collection and distribution. Discussion: Collectively, these studies show the emerging potential for AI applications to enhance food bank and pantry operations. However, notable limitations were identified, including the scarcity of studies on this topic, restricted geographic scopes, and methodological challenges such as the insufficient discussion of data representativeness and statistical power. None of the studies addressed AI ethics, including model bias and fairness, or discussed intervention and policy implications in depth. Further studies should investigate innovative AI-driven solutions within food banks and pantries to help alleviate food insecurity. Full article
(This article belongs to the Special Issue Use of Artificial Intelligence to Fight Malnutrition and Food Insecurity)
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