Criteria2Query 3.0: Leveraging generative large language models for clinical trial eligibility query generation.

ABSTRACT:

Objective

Automated identification of eligible patients is a bottleneck of clinical research. We propose Criteria2Query (C2Q) 3.0, a system that leverages GPT-4 for the semi-automatic transformation of clinical trial eligibility criteria text into executable clinical database queries.

Materials and methods

C2Q 3.0 integrated three GPT-4 prompts for concept extraction, SQL query generation, and reasoning. Each prompt was designed and evaluated separately. The concept extraction prompt was benchmarked against manual annotations from 20 clinical trials by two evaluators, who later also measured SQL generation accuracy and identified errors in GPT-generated SQL queries from 5 clinical trials. The reasoning prompt was assessed by three evaluators on four metrics: readability, cor

SUBMITTER: Park J 

PROVIDER: S-EPMC11129920 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature