Improving Patient Pre-screening for Clinical Trials: Assisting Physicians with Large Language Models

Understand

Physicians considering clinical trials for their patients are met with the laborious process of checking many text based eligibility criteria.

• Large Language Models (LLMs) have shown to perform well for clinical information extraction and clinical reasoning, including medical tests, but not yet in real-world scenarios.
• This paper investigates the use of InstructGPT to assist physicians in determining eligibility for clinical trials based on a patient's summarised medical profile.
• Using a prompting strategy combining one-shot, selection-inference and chain-of-thought techniques, we investigate the performance of LLMs on 10 synthetically created patient profiles.