Large language models in medicine: the potentials and pitfalls

TL;DR

This paper reviews the potential benefits and risks of large language models in healthcare, providing an overview for practitioners to understand their development, applications, and pitfalls in medical contexts.

Contribution

It offers a comprehensive overview and tutorial on LLMs in medicine, highlighting current applications, development, and associated challenges for healthcare practitioners.

Findings

LLMs are increasingly integrated into healthcare applications.

There are significant benefits and potential pitfalls in applying LLMs in medicine.

Understanding LLMs is crucial for safe and effective clinical use.

Abstract

Large language models (LLMs) have been applied to tasks in healthcare, ranging from medical exam questions to responding to patient questions. With increasing institutional partnerships between companies producing LLMs and healthcare systems, real world clinical application is coming closer to reality. As these models gain traction, it is essential for healthcare practitioners to understand what LLMs are, their development, their current and potential applications, and the associated pitfalls when utilized in medicine. This review and accompanying tutorial aim to give an overview of these topics to aid healthcare practitioners in understanding the rapidly changing landscape of LLMs as applied to medicine.