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.

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、患者诊疗及研究开展提供了新途径。本文献计量学综述旨在通过分析2022至2023年间的研究论文与合作网络，全面审视LLMs在BHI中的应用现状。进一步探讨了LLMs如何改进自然语言处理（NLP）在医疗诊断、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，并聚焦该快速演进领域中的重大进展。最后，本文还讨论了LLMs在BHI应用中涉及的伦理问题与实践挑战，例如数据隐私与可靠医疗建议的生成。展望未来，我们探讨了LLMs可能如何进一步变革生物医学研究、医疗服务质量及患者预后。本综述为医疗领域相关方（包括研究人员、临床医生及政策制定者）提供了理解LLMs在BHI中当前状态与未来潜力的重要参考资料。