SynthesisNutrients2025
Artificial Intelligence in Food Bank and Pantry Services: A Systematic Review.
Synthesis in Nutrients, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
BACKGROUND/
objectivesFood 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.
methodsThis 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.
resultsWe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.