Deep Learning for Automatic Upper Airway Obstruction Detection by Analysis of Flow-Volume Curve.

Journal: Respiration; international review of thoracic diseases
PMID:

Abstract

BACKGROUND: Due to the similar symptoms of upper airway obstruction to asthma, misdiagnosis is common. Spirometry is a cost-effective screening test for upper airway obstruction and its characteristic patterns involving fixed, variable intrathoracic and extrathoracic lesions. We aimed to develop a deep learning model to detect upper airway obstruction patterns and compared its performance with that of lung function clinicians.

Authors

  • Yimin Wang
    Department of Electrical Engineering and Computer Science , University of Michigan , 1301 Beal Avenue , Ann Arbor , Michigan 48109-2122 , United States.
  • Yicong Li
    Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, China.
  • Wenya Chen
    National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Changzheng Zhang
    From the School of Electronic Information and Communications, Huazhong University of Science and Technology, South 1st Building, Luoyu Road 1037, Wuhan 430074, China (J.Y., C.H., Y.X.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (M.X., O.A., J.L., T.J., X. Long); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (M.X., O.A., J.L., T.J., X. Long); Department of Radiology, Xin Cai People's Hospital, Xin Cai, China (Changde Li); and Huawei Technologies, Shenzhen, China (D.T., X. Liu, C.Z., Cixing Li).
  • Lijuan Liang
    National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Ruibo Huang
    National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Wenhua Jian
    National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Jianling Liang
    National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
  • Senhua Zhu
    Huawei Cloud BU EI Innovation Laboratory, Huawei Technologies, Shenzhen, China.
  • Dandan Tu
    From the School of Electronic Information and Communications, Huazhong University of Science and Technology, South 1st Building, Luoyu Road 1037, Wuhan 430074, China (J.Y., C.H., Y.X.); Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (M.X., O.A., J.L., T.J., X. Long); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (M.X., O.A., J.L., T.J., X. Long); Department of Radiology, Xin Cai People's Hospital, Xin Cai, China (Changde Li); and Huawei Technologies, Shenzhen, China (D.T., X. Liu, C.Z., Cixing Li).
  • Yi Gao
    Department of Laboratory Medicine, Shengjing Hospital of China Medical University, Shenyang, China.
  • Nanshan Zhong
    Guangzhou National Laboratory, Guangzhou, China.
  • Jinping Zheng
    National Center for Respiratory Medicine, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.