From manual clinical criteria to machine learning algorithms: Comparing outcome endpoints derived from diverse electronic health record data modalities.

Journal: PLOS digital health
Published Date: May 1, 2025

Abstract

BACKGROUND: Progression free survival (PFS) is a critical clinical outcome endpoint during cancer management and treatment evaluation. Yet, PFS is often missing from publicly available datasets due to the current subjective, expert, and time-intensive nature of generating PFS metrics. Given emerging research in multi-modal machine learning (ML), we explored the benefits and challenges associated with mining different electronic health record (EHR) data modalities and automating extraction of PFS metrics via ML algorithms.

Authors

  • Shreya Chappidi
    Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, Bethesda, MD 20892, USA.
  • Mason J Belue
    Medical Research Scholars Program Fellow, Artificial Intelligence Resource, Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
  • Stephanie A Harmon
    Clinical Research Directorate, Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute, Frederick, Maryland, USA.
  • Sarisha Jagasia
    Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
  • Ying Zhuge
    Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Erdal Tasci
    Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, NIH, 9000 Rockville Pike, Building 10, Bethesda, MD 20892, USA.
  • Baris Turkbey
    Molecular Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • Jatinder Singh
    Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Kevin Camphausen
    Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Andra V Krauze
    Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, 20892, USA.

Keywords

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