ReviewFrontiers in nutrition2026
Artificial intelligence-driven personalized dietary recommendations for gastric cancer high-risk populations: a narrative review.
Review in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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Who cites it
2 citing papers in PubMed.
- Beyond weight: a stigma-free, integrated approach to obesity in patients affected by cancer.Reviews in endocrine & metabolic disorders · 2026Review
- Artificial Intelligence-Assisted Design of Plant-Protein Meat Analogues: Integrating Nutrition, Functionality, and Fibrillation-Based Texturization.Comprehensive reviews in food science and food safety · 2026Review
Corrections and comments
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Authors and funding
13 authors.
Funding
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Abstract
This review summarizes the current applications of artificial intelligence (AI) in providing personalized dietary recommendations, and explores its potential applicability to populations at high risk for gastric cancer. Currently, there are no direct intervention trials for gastric cancer patients. However, evidence from metabolic diseases (like diabetes and obesity) shows that AI-driven dietary interventions could be beneficial. This approach may offer translatable benefits for cancer prevention. First, the paper elaborates on the severe incidence of gastric cancer and the limitations of traditional preventive measures, emphasizing the necessity of developing precise and efficient intervention strategies. Subsequently, it systematically outlines methods for identifying high-risk populations and risk stratification (including pathological basis, biomarkers, and genetic risks), as well as the close relationship between dietary patterns (protective and risky) and gastric cancer risk, with a particular focus on the interaction between diet and the gastric microbiome (especially
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