Enhancing systematic literature reviews with generative artificial intelligence: development, applications, and performance evaluation.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 40036547

Abstract

OBJECTIVES: We developed and validated a large language model (LLM)-assisted system for conducting systematic literature reviews in health technology assessment (HTA) submissions.

Authors

  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Surabhi Datta
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Majid Rastegar-Mojarad
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
  • Kyeryoung Lee
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Hunki Paek
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Julie Glasgow
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Chris Liston
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Long He
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Xiaoyan Wang
    Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China.
  • Yingxin Xu
    Regeneron Pharmaceuticals, Inc., Tarrytown, NY 10591, United States.

Keywords

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