Large Language Model Symptom Identification From Clinical Text: Multicenter Study.

Journal: Journal of medical Internet research
Published Date:

Abstract

BACKGROUND: Recognizing patient symptoms is fundamental to medicine, research, and public health. However, symptoms are often underreported in coded formats even though they are routinely documented in physician notes. Large language models (LLMs), noted for their generalizability, could help bridge this gap by mimicking the role of human expert chart reviewers for symptom identification.

Authors

  • Andrew J McMurry
    Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02215, United States.
  • Dylan Phelan
    Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, LM5506, Mail Stop BCH3187, Boston, MA, 02215, United States, 1 617-355-4145.
  • Brian E Dixon
    Regenstrief Institute, Indianapolis, IN, USA.
  • Alon Geva
    Computational Health Informatics Program, Boston Children's Hospital, Boston, Massachusetts, USA.
  • Daniel Gottlieb
    Computational Health Informatics Program, Boston Children's Hospital, Boston, MA, USA.
  • James R Jones
    Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02215, United States.
  • Michael Terry
    Google Health, Palo Alto, California.
  • David E Taylor
    Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.
  • Hannah Callaway
    Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.
  • Sneha Manoharan
    Center for Biomedical Informatics, Regenstrief Institute, Indianapolis, IN, United States.
  • Timothy Miller
    School of Computing and Information Systems, University of Melbourne, Victoria 3010, Australia.
  • Karen L Olson
    Computational Health Informatics Program, Boston Children's Hospital, 401 Park Drive, LM5506, Mail Stop BCH3187, Boston, MA, 02215, United States, 1 617-355-4145.
  • Kenneth D Mandl
    Harvard Medical School, Boston, MA, USA.