AutoCriteria: a generalizable clinical trial eligibility criteria extraction system powered by large language models.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 37952206

Abstract

OBJECTIVES: We aim to build a generalizable information extraction system leveraging large language models to extract granular eligibility criteria information for diverse diseases from free text clinical trial protocol documents. We investigate the model's capability to extract criteria entities along with contextual attributes including values, temporality, and modifiers and present the strengths and limitations of this system.

Authors

  • Surabhi Datta
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Kyeryoung Lee
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Hunki Paek
    IMO Health, Inc., Rosemont, IL 60018, United States.
  • Frank J Manion
    School of Biomedical Informatics, University of Texas Health Science Center, Houston, Texas, United States.
  • Nneka Ofoegbu
    Melax Technologies, Houston, TX 77030, United States.
  • Jingcheng Du
    University of Texas Health Science Center at Houston, Houston, Texas, USA.
  • Ying Li
    School of Information Engineering, Chang'an University, Xi'an 710010, China.
  • Liang-Chin Huang
    School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Jingqi Wang
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Bin Lin
    Department of Biostatistics, Hospital for Special Surgery, 535 E 70(th) Street, New York, NY 10021, United States of America.
  • Hua Xu
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiaoyan Wang
    Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China.

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