Large language models in food and nutrition science: Opportunities, challenges, and the case of FoodyLLM

Background: Reliable nutrient profiling and semantic interoperability are essential for scalable dietary assessment, food labeling (e.g., traffic-light schemes), and FAIR integration of food composition and consumption data. However, general-purpose large language models (LLMs) are not systematicall...

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Autori principali:	Ana Gjorgjevikj, Matej Martinc, Gjorgjina Cenikj, Riste Stojanov, Jan Drole, Gordana Ispirova, Giulia Menichetti, Nives Ogrinc, Dimitar Trajanov, Sašo Džeroski, Barbara Koroušić Seljak, Tome Eftimov
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2026-01-01
Serie:	Current Research in Food Science
Soggetti:	FoodyLLM FAIR data Nutrient estimation Healthy diet Large language model
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2665927126000511
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