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Large language models in health care: Development, applications, and challenges.
Yang, Rui; Tan, Ting Fang; Lu, Wei; Thirunavukarasu, Arun James; Ting, Daniel Shu Wei; Liu, Nan.
Afiliação
  • Yang R; Department of Biomedical Informatics, Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore.
  • Tan TF; Singapore National Eye Center, Singapore Eye Research Institute Singapore Health Service Singapore Singapore.
  • Lu W; StatNLP Research Group Singapore University of Technology and Design Singapore.
  • Thirunavukarasu AJ; University of Cambridge School of Clinical Medicine Cambridge UK.
  • Ting DSW; Singapore National Eye Center, Singapore Eye Research Institute Singapore Health Service Singapore Singapore.
  • Liu N; Duke-NUS Medical School Centre for Quantitative Medicine Singapore Singapore.
Health Care Sci ; 2(4): 255-263, 2023 Aug.
Article em En | MEDLINE | ID: mdl-38939520
ABSTRACT
Recently, the emergence of ChatGPT, an artificial intelligence chatbot developed by OpenAI, has attracted significant attention due to its exceptional language comprehension and content generation capabilities, highlighting the immense potential of large language models (LLMs). LLMs have become a burgeoning hotspot across many fields, including health care. Within health care, LLMs may be classified into LLMs for the biomedical domain and LLMs for the clinical domain based on the corpora used for pre-training. In the last 3 years, these domain-specific LLMs have demonstrated exceptional performance on multiple natural language processing tasks, surpassing the performance of general LLMs as well. This not only emphasizes the significance of developing dedicated LLMs for the specific domains, but also raises expectations for their applications in health care. We believe that LLMs may be used widely in preconsultation, diagnosis, and management, with appropriate development and supervision. Additionally, LLMs hold tremendous promise in assisting with medical education, medical writing and other related applications. Likewise, health care systems must recognize and address the challenges posed by LLMs.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article