ArticleInternational journal of food science2026
A Multinutrient Clustering Framework for Personalized Food Recommendations.
Article in International journal of food science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- A Multinutrient Clustering Framework for Personalized Food Recommendations.International journal of food science · 2026Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Personalized nutrition recommendations encounter difficulties in aligning users' dietary preferences with appropriate foods in extensive nutritional databases comprising thousands of products. This research introduces a multinutrient clustering framework that examines 8790 foods from the USDA National Nutrient Database for Standard Reference, Release 28, utilizing 23 nutritional attributes, including macronutrients, vitamins, and minerals. We thoroughly analyze
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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.