A systematic assessment of large language models’ knowledge of rare diseases: How much do large language models know about rare disease?

Summary: Large language models (LLMs) perform well on general medical benchmarks, but their ability to reason about rare diseases (RDs) remains unclear. Rather than challenge LLMs to diagnose a limited number of cases that are unlikely to represent all RDs or RD-associated genes, we instead sought t...

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Bibliografiska uppgifter

Huvudupphov:	Tudor Groza, Allison J. Marcello, Tristan Carlisle, Weng Khong Lim, Melissa Haendel, Neerja Karnani, Peter N. Robinson, Holm Graessner, Jessica X. Chong, Gareth Baynam, Saumya Shekhar Jamuar
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	Elsevier 2026-01-01
Serie:	HGG Advances
Ämnen:	rare disease structured knowledge Human Phenotype Ontology rare disease HPO annotations rare disease gene annotations large language models
Länkar:	http://www.sciencedirect.com/science/article/pii/S2666247725001617
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