Large language models for automating clinical trial matching.

Journal: Current opinion in urology
PMID: 40114652

Abstract

PURPOSE OF REVIEW: The uses of generative artificial intelligence (GAI) technologies in medicine are expanding, with the use of large language models (LLMs) for matching patients to clinical trials of particular interest. This review provides an overview of the current ability of leveraging LLMs for clinical trial matching.

Authors

  • Ethan Layne
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Claire Olivas
    USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine.
  • Jacob Hershenhouse
    USC Institute of Urology and Catherine and Joseph Aresty Department of Urology, Keck School of Medicine.
  • Conner Ganjavi
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Francesco Cei
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Inderbir Gill
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Giovanni E Cacciamani
    USC Institute of Urology, Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA - giovanni.cacciamani@med.usc.edu.

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