AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models.

ABSTRACT:

Objectives

We aim to build a generalizable information extraction system leveraging large language models to extract granular eligibility criteria information for diverse diseases from free text clinical trial protocol documents. We investigate the model's capability to extract criteria entities along with contextual attributes including values, temporality, and modifiers and present the strengths and limitations of this system.

Materials and methods

The clinical trial data were acquired from https://ClinicalTrials.gov/. We developed a system, AutoCriteria, which comprises the following modules: preprocessing, knowledge ingestion, prompt modeling based on GPT, postprocessing, and interim evaluation. The final system evaluation was performed, both quantitatively and qualitati

SUBMITTER: Datta S 

PROVIDER: S-EPMC10797270 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature