Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data.

Journal: JAMA network open
Published Date: Dec 1, 2022

Abstract

IMPORTANCE: Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest radiograph images and commonly available electronic medical record (EMR) data, may enable automated identification of high-risk patients as a step toward improving lung cancer screening participation.

Authors

  • Vineet K Raghu
    Department of Computer Science, University of Pittsburgh, Pittsburgh, PA, USA.
  • Anika S Walia
    Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts.
  • Aniket N Zinzuwadia
    Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts.
  • Reece J Goiffon
    Division of Abdominal Imaging, Department of Radiology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts.
  • Jo-Anne O Shepard
    Division of Thoracic Imaging and Intervention, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
  • Hugo J W L Aerts
    Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States.
  • Inga T Lennes
    Department of Medicine, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, 25 Shattuck Street, Boston, MA, USA. Electronic address: ilennes@partners.org.
  • Michael T Lu
    Cardiovascular Imaging Research Center, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston.

Keywords

External Resources

Popular Topics
Recent Journals