TRACE: applying AI language models to extract ancestry information from curated biomedical literature.

ABSTRACT:

Introduction

Ancestry reporting is essential to ensure transparency and proper representation in biomedical studies. However, manually extracting this information from study texts is time-consuming and inefficient. In this paper, we present TRACE (Tool for Researching Ancestry and Cell Extraction), powered by GPT-4 and web-crawling, to automate ancestry identification by detecting cell lines or cultures in texts and tracing their ancestry.

Methods

TRACE extracts cell lines and primary cultures from research articles and follows web sources to determine their ancestry. We compared TRACE's outputs to a manually generated database to confirm its performance in identifying and verifying ancestry information.

Results

The results reveal an overrepresentation of European/Whi

SUBMITTER: Veintimilla AM 

PROVIDER: S-EPMC12491185 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature