Large Language Models (LLMs) have rapidly become important tools in
Biomedical and Health Informatics (BHI), enabling new ways to analyze data,
treat patients, and conduct research. This bibliometric review aims to provide
a panoramic view of how LLMs have been used in BHI by examining research
articles and collaboration networks from 2022 to 2023. It further explores how
LLMs can improve Natural Language Processing (NLP) applications in various BHI
areas like medical diagnosis, patient engagement, electronic health record
management, and personalized medicine. To do this, our bibliometric review
identifies key trends, maps out research networks, and highlights major
developments in this fast-moving field. Lastly, it discusses the ethical
concerns and practical challenges of using LLMs in BHI, such as data privacy
and reliable medical recommendations. Looking ahead, we consider how LLMs could
further transform biomedical research as well as healthcare delivery and
patient outcomes. This comprehensive review serves as a resource for
stakeholders in healthcare, including researchers, clinicians, and
policymakers, to understand the current state and future potential of LLMs in
BHI.

大型语言模型（LLMs）已经迅速成为生物医学和健康信息学（BHI）中重要的工具，通过检查 2022 年至 2023 年的研究文章和合作网络，本文献计量回顾旨在全面了解 LLMs 在 BHI 中的应用情况。它进一步探讨了 LLMs 如何改善医疗诊断、患者参与、电子健康档案管理和个性化医学等 BHI 领域的自然语言处理（NLP）应用。同时，它还讨论了在 BHI 中使用 LLMs 所面临的伦理关切和实际挑战，比如数据隐私和可靠的医疗建议。展望未来，我们考虑 LLMs 如何进一步改变生物医学研究以及医疗服务和患者结果。该综合回顾对于了解生物医学和健康信息学中 LLMs 的当前状态和未来潜力的相关人员，包括研究人员、临床医生和决策者，具有重要价值。