Large language models (LLMs), such as ChatGPT, have received substantial attention due to their capabilities for understanding and generating human language. LLMs in medicine to assist physicians for patient care are emerging as a promising research direction in both artificial intelligence and clinical medicine. This review provides a comprehensive overview of the principles, applications, and challenges faced by LLMs in medicine. We address the following specific questions: 1) How should medical LLMs be built? 2) What are the measures for the downstream performance of medical LLMs? 3) How should medical LLMs be utilized in real-world clinical practice? 4) What challenges arise from the use of medical LLMs? and 5) How should we better construct and utilize medical LLMs? This review aims to provide insights into the opportunities and challenges of LLMs in medicine, and serve as a practical resource for constructing effective medical LLMs. We also maintain and regularly updated list of practical guides on medical LLMs at https://github.com/AI-in-Health/MedLLMsPracticalGuide.

翻译：大语言模型（LLMs），如ChatGPT，因其理解和生成人类语言的能力而受到广泛关注。在医学领域，利用LLMs辅助医生进行患者护理正成为人工智能和临床医学中一个充满前景的研究方向。本综述全面概述了医学领域LLMs的原理、应用及面临的挑战。我们聚焦以下具体问题：1) 如何构建医学LLMs？2) 医学LLMs的下游性能应如何衡量？3) 在实际临床实践中应如何应用医学LLMs？4) 使用医学LLMs会引发哪些挑战？5) 应如何更好地构建和利用医学LLMs？本综述旨在为医学领域LLMs的机遇和挑战提供见解，并作为构建有效医学LLMs的实用资源。我们还维护并定期更新一份医学LLMs实用指南清单，地址为：https://github.com/AI-in-Health/MedLLMsPracticalGuide。