Smart chest X-ray worklist prioritization using artificial intelligence: a clinical workflow simulation.

Journal: European radiology
Published Date: Nov 21, 2020

Abstract

OBJECTIVE: The aim is to evaluate whether smart worklist prioritization by artificial intelligence (AI) can optimize the radiology workflow and reduce report turnaround times (RTATs) for critical findings in chest radiographs (CXRs). Furthermore, we investigate a method to counteract the effect of false negative predictions by AI-resulting in an extremely and dangerously long RTAT, as CXRs are sorted to the end of the worklist.

Authors

  • Ivo Baltruschat
  • Leonhard Steinmeister
    Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Hannes Nickisch
    Philips Medical Systems Technologies Ltd., Advanced Technologies Center, Haifa, 3100202, Israel.
  • Axel Saalbach
    Philips Research, Hamburg, Germany.
  • Michael Grass
    Philips Research, Hamburg, Germany.
  • Gerhard Adam
    Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
  • Tobias Knopp
    Institute for Biomedical Imaging, Hamburg University of Technology, Hamburg, Germany.
  • Harald Ittrich
    Department for Diagnostic and Interventional Radiology and Nuclear Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

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