Automated Matching of Patients to Clinical Trials: A Patient-Centric Natural Language Processing Approach for Pediatric Leukemia.

Journal: JCO clinical cancer informatics
PMID: 37428994

Abstract

PURPOSE: Matching patients to clinical trials is cumbersome and costly. Attempts have been made to automate the matching process; however, most have used a trial-centric approach, which focuses on a single trial. In this study, we developed a patient-centric matching tool that matches patient-specific demographic and clinical information with free-text clinical trial inclusion and exclusion criteria extracted using natural language processing to return a list of relevant clinical trials ordered by the patient's likelihood of eligibility.

Authors

  • Samuel Kaskovich
    Emergency Medicine Residency, Denver Health, Denver, CO.
  • Kirk D Wyatt
    Division of Pediatric Hematology/Oncology, Department of Pediatric and Adolescent Medicine, Mayo Clinic, Minnesota, United States.
  • Tomasz Oliwa
    The University of Chicago, Chicago, IL.
  • Luca Graglia
    Department of Pediatrics, University of Chicago, Chicago, IL.
  • Brian Furner
    Pediatrics, University of Chicago, Chicago, IL, USA.
  • Jooho Lee
    Department of Pediatrics, University of Chicago, Chicago, IL.
  • Anoop Mayampurath
    Department of Medicine, University of Wisconsin-Madison, Madison, WI, United States.
  • Samuel L Volchenboum
    The University of Chicago, Chicago, IL.

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