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 bibliometric 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.

翻译：大型语言模型（LLMs）已迅速成为生物医学与健康信息学（BHI）领域的重要工具，为数据分析、患者诊疗和科研活动开辟了新途径。本文献计量综述旨在通过考察2022至2023年的研究论文与合作网络，全景式呈现LLMs在BHI中的应用现状。进一步探讨了LLMs如何改进医疗诊断、患者参与、电子健康档案管理、个性化医疗等BHI领域中的自然语言处理（NLP）应用。为此，我们通过文献计量分析识别关键趋势、绘制研究网络图谱，并突出该快速发展领域的主要进展。最后，本研究讨论了LLMs在BHI中应用的伦理关切与实践挑战，如数据隐私和可靠医疗建议问题。展望未来，我们思考了LLMs将如何进一步推动生物医学研究、医疗服务交付及患者预后改善。本综述可为包括研究人员、临床医生和政策制定者在内的医疗健康利益相关者提供参考，以理解LLMs在BHI中的当前状态与未来潜力。