Large language models in medicine: the potentials and pitfalls
It provides an overview for healthcare practitioners on LLMs in medicine, but is incremental as it synthesizes existing knowledge without new findings.
This review addresses the application of large language models (LLMs) in healthcare, covering tasks like medical exams and patient interactions, and highlights the need for practitioners to understand their potentials and pitfalls as clinical use grows.
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.