Large language models improve clinical decision making of medical students through patient simulation and structured feedback: a randomized controlled trial.

ABSTRACT:

Background

Clinical decision-making (CDM) refers to physicians' ability to gather, evaluate, and interpret relevant diagnostic information. An integral component of CDM is the medical history conversation, traditionally practiced on real or simulated patients. In this study, we explored the potential of using Large Language Models (LLM) to simulate patient-doctor interactions and provide structured feedback.

Methods

We developed AI prompts to simulate patients with different symptoms, engaging in realistic medical history conversations. In our double-blind randomized design, the control group participated in simulated medical history conversations with AI patients (control group), while the intervention group, in addition to simulated conversations, also received AI-generate

SUBMITTER: Brugge E 

PROVIDER: S-EPMC11605890 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature