Automating the data extraction process for systematic reviews using GPT-4o and o3.

ABSTRACT: Large language models have shown promise for automating data extraction (DE) in systematic reviews (SRs), but most existing approaches require manual interaction. We developed an open-source system using GPT-4o to automatically extract data with no human intervention during the extraction process. We developed the system on a dataset of 290 randomized controlled trials (RCTs) from a published SR about cognitive behavioral therapy for insomnia. We evaluated the system on two other datasets: 5 RCTs from an updated search for the same review and 10 RCTs used in a separate published study that had also evaluated automated DE. We developed the best approach across all variables in the development dataset using GPT-4o. The performance in the updated-search dataset using o3 was 74.9% sensitivity,

SUBMITTER: Kataoka Y 

PROVIDER: S-EPMC12823200 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature