Artificial Intelligence Algorithm Detecting Lung Infection in Supine Chest Radiographs of Critically Ill Patients With a Diagnostic Accuracy Similar to Board-Certified Radiologists.

Journal: Critical care medicine
PMID: 32433121

Abstract

OBJECTIVES: Interpretation of lung opacities in ICU supine chest radiographs remains challenging. We evaluated a prototype artificial intelligence algorithm to classify basal lung opacities according to underlying pathologies.

Authors

  • Johannes Rueckel
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Wolfgang G Kunz
    Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich, Germany.
  • Boj F Hoppe
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Maximilian Patzig
    Institute of Diagnostic and Interventional Neuroradiology, University Hospital, LMU Munich, Munich, Germany.
  • Mike Notohamiprodjo
    Department of Diagnostic and Interventional Radiology, University Hospital Tuebingen, Tuebingen, Germany.
  • Felix G Meinel
    Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, United States; Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital, Munich, Germany.
  • Clemens C Cyran
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.
  • Michael Ingrisch
    Department of Radiology, Ludwig-Maximilians-University Munich, Munich, Germany.
  • Jens Ricke
    Department of Radiology, University Hospital Munich, Germany. Electronic address: jens.ricke@med.uni-muenchen.de.
  • Bastian O Sabel
    Department of Radiology, University Hospital, LMU Munich, Munich, Germany.

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