Matching Patients to Clinical Trials with Large Language Models

arXiv:2307.15051v3 Announce Type: replace
Abstract: Clinical trials are often hindered by the challenge of patient recruitment. In this work, we introduce TrialGPT, a first-of-its-kind large language model (LLM) framework to assist patient-to-trial matching. Given a patient note, TrialGPT predicts the patient's eligibility on a criterion-by-criterion basis and then consolidates these predictions to assess the patient's eligibility for the target trial. We evaluate the trial-level prediction performance of TrialGPT on three publicly available cohorts of 184 patients with over 18,000 trial …

abstract arxiv challenge clinical clinical trials criterion cs.ai cs.cl framework kind language language model language models large language large language model large language models llm patient patients predictions recruitment type work