Back to search

Article

A Systematic Exploration of LLM Behavior for EHR Phenotyping

2026-04-24

Abstract excerpt

<h4>Background</h4> Electronic health record (EHR) phenotyping underpins observational research, cohort discovery, and clinical trial screening. Large language models (LLMs) offer new ca-pabilities for extracting phenotypes from unstructured text, but their performance depends on pipeline design choices-including prompting, text segmentation, and aggregation. No systematic framework has previously examined how th...

Topics

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

Identifiers and source

Literature Corpus work
50d885aa-b1fb-5837-aef7-163f0aebe5c2
DOI
10.64898/2026.04.16.26350890
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.
A Systematic Exploration of LLM Behavior for EHR PhenotypingDOI 10.64898/2026.04.16.26350890
Select a neighboring publication to make it the new centre.