ArticleScientific reports2023
From language models to large-scale food and biomedical knowledge graphs.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Next-generation probiotics: an outlook into current applications and future developments.Nature reviews. Microbiology · 2026Review
- Large language models in food and nutrition science: Opportunities, challenges, and the case of FoodyLLM.Current research in food science · 2026Article
- The networks of ingredient combinations as culinary fingerprints of world cuisines.NPJ science of food · 2025Article
- LSD600: the first corpus of biomedical abstracts annotated with lifestyle-disease relations.Database : the journal of biological databases and curation · 2025Article
- Augmented non-hallucinating large language models as medical information curators.NPJ digital medicine · 2024Article
- NutriBase - management system for the integration and interoperability of food- and nutrition-related data and knowledge.Frontiers in nutrition · 2024Article
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Authors and funding
6 authors.
Funding
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Abstract
Knowledge about the interactions between dietary and biomedical factors is scattered throughout uncountable research articles in an unstructured form (e.g., text, images, etc.) and requires automatic structuring so that it can be provided to medical professionals in a suitable format. Various biomedical knowledge graphs exist, however, they require further extension with relations between food and biomedical entities. In this study, we evaluate the performance of three state-of-the-art relation-mining pipelines (FooDis, FoodChem and ChemDis) which extract relations between food, chemical and disease entities from textual data. We perform two case studies, where relations were automatically extracted by the pipelines and validated by domain experts. The results show that the pipelines can extract relations with an average precision around 70%, making new discoveries available to domain experts with reduced human effort, since the domain experts should only evaluate the results, instead of finding, and reading all new scientific papers.
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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.