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、患者诊疗及科学研究开辟了新途径。本文献计量综述旨在通过考察2022至2023年间的研究论文与合作网络，全面呈现LLMs在BHI中的应用全景。进一步，它探讨了LLMs如何提升自然语言处理（NLP）在BHI各子领域（如医学诊断、患者互动、电子健康记录管理及个性化医疗）中的应用效能。为此，本综述识别了关键趋势，绘制了研究网络图谱，并突显了这一快速发展领域中的重大进展。最后，本文讨论了在BHI中应用LLMs所涉及的伦理关切与实践挑战，例如数据隐私保护及可靠医疗建议生成。展望未来，我们思考了LLMs如何进一步变革生物医学研究、医疗服务交付及患者预后。本文献计量综述旨在为医疗领域的利益相关者（包括研究人员、临床医生及政策制定者）提供参考资源，以理解LLMs在BHI中的当前状态与未来潜力。