Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs.

Journal: Journal of thoracic imaging
Published Date:

Abstract

PURPOSE: To evaluate the performance of a deep learning (DL) algorithm for the detection of COVID-19 on chest radiographs (CXR).

Authors

  • Wan Hang Keith Chiu
    Medical Artificial Intelligence Laboratory Program (MAIL), Department of Diagnostic Radiology, LKS Faculty of Medicine.
  • Varut Vardhanabhuti
    Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, China.
  • Dmytro Poplavskiy
    , Brisbane, Queensland, Australia.
  • Philip Leung Ho Yu
    Department of Statistics and Actuarial Sciences.
  • Richard Du
    Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.
  • Alistair Yun Hee Yap
    Medical Artificial Intelligence Laboratory Program (MAIL), Department of Diagnostic Radiology, LKS Faculty of Medicine.
  • Sailong Zhang
    Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.
  • Ambrose Ho-Tung Fong
    Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR.
  • Thomas Wing-Yan Chin
    Department of Radiology and Imaging, Queen Elizabeth Hospital.
  • Jonan Chun Yin Lee
    Department of Radiology and Imaging, Queen Elizabeth Hospital.
  • Siu Ting Leung
    Department of Radiology, Pamela Youde Nethersole Eastern Hospital.
  • Christine Shing Yen Lo
    Department of Radiology, Queen Mary Hospital.
  • Macy Mei-Sze Lui
    Department of Medicine, Queen Mary Hospital, Hong Kong, Hong Kong SAR.
  • Benjamin Xin Hao Fang
    Department of Radiology, Queen Mary Hospital.
  • Ming-Yen Ng
    Medical Artificial Intelligence Laboratory Program (MAIL), Department of Diagnostic Radiology, LKS Faculty of Medicine.
  • Michael D Kuo
    Department of Radiology, The University of Hong Kong, Hong Kong, China.