Article

Large language models and retrieval augmented generation for complex clinical codelists: evaluating performance and assessing failure modes

2026-04-24

Abstract excerpt

<h4>Objectives</h4> Large language models (LLMs) have shown promise in creating clinical codelists for research purposes, a time-consuming task requiring expert domain knowledge. Here, we evaluate the performance and assess failure modes of a retrieval augmented generation (RAG) approach to creating clinical codelists for the large and complex medical terminology used by the Clinical Practice Research Datalink (C...

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Genomics and Rare Diseases

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Literature Corpus work: 3bc98f47-82b0-54de-ae81-c78f37cbb4d0
DOI: 10.64898/2026.04.23.26351098

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