A Deep-Learning Diagnostic Support System for the Detection of COVID-19 Using Chest Radiographs: A Multireader Validation Study.

Journal: Investigative radiology
Published Date: Jun 1, 2021

Abstract

MATERIALS AND METHODS: Five publicly available databases comprising normal CXR, confirmed COVID-19 pneumonia cases, and other pneumonias were used. After the harmonization of the data, the training set included 7966 normal cases, 5451 with other pneumonia, and 258 CXRs with COVID-19 pneumonia, whereas in the testing data set, each category was represented by 100 cases. Eleven blinded radiologists with various levels of expertise independently read the testing data set. The data were analyzed separately with the newly proposed artificial intelligence-based system and by consultant radiologists and residents, with respect to positive predictive value (PPV), sensitivity, and F-score (harmonic mean for PPV and sensitivity). The χ2 test was used to compare the sensitivity, specificity, accuracy, PPV, and F-scores of the readers and the system.

Authors

  • Matthias Fontanellaz
    From the ARTORG Center for Biomedical Engineering Research, University of Bern.
  • Lukas Ebner
  • Adrian Huber
    Department of Diagnostic, Interventional and Pediatric Radiology, University Hospital and University of Bern, Freiburgstrasse, CH-3010 Bern, Switzerland.
  • Alan Peters
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital.
  • Laura Löbelenz
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital.
  • Cynthia Hourscht
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital.
  • Jeremias Klaus
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital.
  • Jaro Munz
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital.
  • Thomas Ruder
    Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital.
  • Dionysios Drakopoulos
    From the Departments of Diagnostic, Interventional, and Pediatric Radiology.
  • Dominik Sieron
    Department of Radiology, Division City and County Hospitals, Inselgroup, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Elias Primetis
    Department of Radiology, Division City and County Hospitals, Inselgroup, Bern University Hospital, University of Bern, Bern, Switzerland.
  • Johannes T Heverhagen
    From the Departments of Diagnostic, Interventional, and Pediatric Radiology.
  • Stavroula Mougiakakou
  • Andreas Christe

Keywords

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