A large language model-based generative natural language processing framework fine-tuned on clinical notes accurately extracts headache frequency from electronic health records.

Journal: Headache
PMID:

Abstract

OBJECTIVE: To develop a natural language processing (NLP) algorithm that can accurately extract headache frequency from free-text clinical notes.

Authors

  • Chia-Chun Chiang
  • Man Luo
    School of Art and Design, Shanghai University of Engineering Science, Shanghai, 201620, PR. China.
  • Gina Dumkrieger
    Department of Neurology, Mayo Clinic, Phoenix, Arizona, USA.
  • Shubham Trivedi
    Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA.
  • Yi-Chieh Chen
    Department of Pharmacy, Mayo Clinic, Rochester, Minnesota, USA.
  • Chieh-Ju Chao
    Department of Radiology, Radiology Informatics Lab, Mayo Clinic, Rochester, MN 55905, United States.
  • Todd J Schwedt
    Department of Neurology, Mayo Clinic, Scottsdale, Arizona, United States of America.
  • Abeed Sarker
    Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.
  • Imon Banerjee
    Mayo Clinic, Department of Radiology, Scottsdale, AZ, USA.