A real-world evaluation of the diagnostic accuracy of radiologists using positive predictive values verified from deep learning and natural language processing chest algorithms deployed retrospectively.

Journal: BJR open
Published Date: Dec 12, 2023

Abstract

OBJECTIVES: This diagnostic study assessed the accuracy of radiologists retrospectively, using the deep learning and natural language processing chest algorithms implemented in Clinical Review version 3.2 for: pneumothorax, rib fractures in digital chest X-ray radiographs (CXR); aortic aneurysm, pulmonary nodules, emphysema, and pulmonary embolism in CT images.

Authors

  • Bahadar S Bhatia
    Directorate of Diagnostic Radiology, Sandwell & West Birmingham NHS Trust, Lyndon, West Bromwich B71 4HJ, United Kingdom.
  • John F Morlese
    Directorate of Diagnostic Radiology, Sandwell & West Birmingham NHS Trust, Lyndon, West Bromwich B71 4HJ, United Kingdom.
  • Sarah Yusuf
    Directorate of Diagnostic Radiology, Sandwell & West Birmingham NHS Trust, Lyndon, West Bromwich B71 4HJ, United Kingdom.
  • Yiting Xie
    Merge, Merative (Formerly, IBM Watson Health Imaging), Ann Arbor, Michigan, MI 48108, United States.
  • Bob Schallhorn
    Merge, Merative (Formerly, IBM Watson Health Imaging), Ann Arbor, Michigan, MI 48108, United States.
  • David Gruen
    Jefferson Radiology and Radiology Partners, 111 Founders Plaza, East Hartford, Connecticut CT 06108, United States.

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