Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography.

Journal: Occupational and environmental medicine
PMID: 32471837

Abstract

OBJECTIVES: To investigate the potential of deep learning in assessing pneumoconiosis depicted on digital chest radiographs and to compare its performance with certified radiologists.

Authors

  • Xiaohua Wang
    Department of Radiology, Peking University Third Hospital, Beijing, China.
  • Juezhao Yu
    Departments of Radiology and Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Qiao Zhu
    Department of Radiology, Peking University Third Hospital, Beijing, China.
  • Shuqiang Li
    Department of Occupational Disease, Peking University Third Hospital, Beijing, China.
  • Zanmei Zhao
    Department of Occupational Disease, Peking University Third Hospital, Beijing, China.
  • Bohan Yang
    Departments of Radiology and Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
  • Jiantao Pu
    Department of Radiology, University of Pittsburgh, Pittsburgh, PA, 15213, USA.

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