Identification of Patients With Metastatic Prostate Cancer With Natural Language Processing and Machine Learning.

Journal: JCO clinical cancer informatics
Published Date: Oct 1, 2022

Abstract

PURPOSE: Understanding treatment patterns and effectiveness for patients with metastatic prostate cancer (mPCa) is dependent on accurate assessment of metastatic status. The objective was to develop a natural language processing (NLP) model for identifying patients with mPCa and evaluate the model's performance against chart-reviewed data and an International Classification of Diseases (ICD) 9/10 code-based method.

Authors

  • Ruixin Yang
    Urology Section, Department of Surgery, Veterans Affairs Health Care System, Durham, NC.
  • Di Zhu
    Urology Section, Department of Surgery, Veterans Affairs Health Care System, Durham, NC.
  • Lauren E Howard
    Urology Section, Veterans Affairs Medical Center, Durham, North Carolina, USA.
  • Amanda De Hoedt
    Urology Section, Department of Surgery, Veterans Affairs Health Care System, Durham, NC.
  • Stephen B Williams
    Division of Urology, Department of Surgery, The University of Texas Medical Branch, Galveston, TX.
  • Stephen J Freedland
    Surgery Section, Durham Veterans Administration, and Division of Urology, Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, California.
  • Zachary Klaassen
    Division of Urology, Medical College of Georgia - Augusta University, Augusta, GA; Georgia Cancer Center, Augusta, GA.

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