Back to search

Article

Evaluating Large Language Models for Translating Multimodal Phenotype Documentations into Executable EHR Phenotyping Algorithms

2026-05-26

Abstract excerpt

<title>Abstract</title> <p>Research applications of electronic health record (EHR) phenotypes require translating clinical definitions into executable EHR database queries, a labor-intensive process. We evaluated two frontier large language models across five phenotypes and three documentation modalities. Both models captured high-level logic from structured text but degraded markedly with diagram-only input. Err...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
3fae2e5c-7ff6-569a-a888-3eef362925c9
DOI
10.21203/rs.3.rs-9719613/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Evaluating Large Language Models for Translating Multimodal Phenotype Documentations into Executable EHR Phenotyping AlgorithmsDOI 10.21203/rs.3.rs-9719613/v1
Select a neighboring publication to make it the new centre.