A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study.

Journal: PloS one
Published Date: Jan 1, 2020

Abstract

BACKGROUND: To date, the missed diagnosis rate of pulmonary hypertension (PH) was high, and there has been limited development of a rapid, simple, and effective way to screen the disease. The purpose of this study is to develop a deep learning approach to achieve rapid detection of possible abnormalities in chest radiographs suggesting PH for screening patients suspected of PH.

Authors

  • Xiao-Ling Zou
    Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.
  • Yong Ren
    Artificial Intelligence Innovation Center, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
  • Ding-Yun Feng
    Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.
  • Xu-Qi He
    Department of Medical Ultrasound, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Yue-Fei Guo
    Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Hai-Ling Yang
    Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.
  • Xian Li
    Laboratory of Fruit Quality Biology, Zhejiang Provincial Key Laboratory of Horticultural Plant Integrative Biology, The State Agriculture Ministry Laboratory of Horticultural Plant Growth, Development and Quality Improvement, Zhejiang University, Hangzhou 310058, China.
  • Jia Fang
    Department of Pumonary Diseases, Dongguan Tangxia Hospital, Dongguan, China.
  • Quan Li
  • Jun-Jie Ye
    Center for Artificial Intelligence in Medicine, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
  • Lan-Qing Han
    Center for Artificial Intelligence in Medicine, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
  • Tian-Tuo Zhang
    Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.

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