Large Language Models in Biomedical and Health Informatics: A Bibliometric Review
CoRR(2024)
摘要
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.
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