Natural Language Processing for Digital Health in the Era of Large Language Models.

Journal: Yearbook of medical informatics
PMID: 40199310

Abstract

OBJECTIVES: Large language models (LLMs) are revolutionizing the natural language pro-cessing (NLP) landscape within healthcare, prompting the need to synthesize the latest ad-vancements and their diverse medical applications. We attempt to summarize the current state of research in this rapidly evolving space.

Authors

  • Abeed Sarker
    Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.
  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Yanshan Wang
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
  • Yunyu Xiao
    Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • Sudeshna Das
    Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Dalton Schutte
    Institute for Health Informatics, University of Minnesota, Minneapolis, MN, USA; Department of Pharmaceutical Care & Health Systems, University of Minnesota, Minneapolis, MN, USA.
  • David Oniani
    Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.
  • Qianqian Xie
    Department of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT 06510, United States.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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