Large language models for extracting histopathologic diagnoses of colorectal cancer and dysplasia from electronic health records.

ABSTRACT:

Background

Accurate data resources are essential for impactful medical research, but available structured datasets are often incomplete or inaccurate. Recent advances in open-weight large language models (LLMs) enable more accurate data extraction from unstructured text in electronic health records (EHRs) but have not yet been thoroughly validated for challenging diagnoses such as inflammatory bowel disease (IBD)-related neoplasia.

Objective

Create a validated approach using LLMs for identifying histopathologic diagnoses in pathology reports from the nationwide Veterans Health Administration database, including patients with genotype data within the Million Veteran Program (MVP) biobank.

Design

Our approach utilizes simple 'yes/no' question prompts for following pheno

SUBMITTER: Johnson B 

PROVIDER: S-EPMC12045448 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature