Generative AI in Medicine

TL;DR

This paper reviews the expanding role of generative AI in medicine, highlighting its applications, challenges like privacy and transparency, and future research directions to harness its full potential.

Contribution

It provides a comprehensive overview of generative AI applications in medicine and discusses key challenges and open research questions.

Findings

Generative AI has diverse applications in clinical settings.

Major challenges include privacy, transparency, and equity.

Open research directions are identified for future development.

Abstract

The increased capabilities of generative AI have dramatically expanded its possible use cases in medicine. We provide a comprehensive overview of generative AI use cases for clinicians, patients, clinical trial organizers, researchers, and trainees. We then discuss the many challenges -- including maintaining privacy and security, improving transparency and interpretability, upholding equity, and rigorously evaluating models -- which must be overcome to realize this potential, and the open research directions they give rise to.