Validation of Non-Small Cell Lung Cancer Clinical Insights Using a Generalized Oncology Natural Language Processing Model.

Journal: JCO clinical cancer informatics
Published Date: Sep 1, 2024

Abstract

PURPOSE: Limited studies have used natural language processing (NLP) in the context of non-small cell lung cancer (NSCLC). This study aimed to validate the application of an NLP model to an NSCLC cohort by extracting NSCLC concepts from free-text medical notes and converting them to structured, interpretable data.

Authors

  • Rachel C Kenney
  • Xiaoren Chen
    Optum Insight, Optum, Eden Prairie, MN.
  • Kazuki Shintani
    Optum Insight, Optum, Eden Prairie, MN.
  • Clara Gagnon
    Optum Insight, Optum, Eden Prairie, MN.
  • John Liu
    Department of Neurological Surgery, Keck School of Medicine of University of Southern California, 1200 North State St., Suite 3300, Los Angeles, CA, 90033, USA.
  • Stacey DaCosta Byfield
    Optum Labs, Optum, Eden Prairie, MN.
  • Lorre Ochs
    Optum Insight, Optum, Eden Prairie, MN.
  • Anne-Marie Currie
    Optum Insight, Optum, Eden Prairie, MN.

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