Development, deployment, and feature interpretability of a three-class prediction model for pulmonary diseases.

Journal: Insights into imaging
Published Date:

Abstract

PURPOSE: To develop a high-performance machine learning model for predicting and interpreting features of pulmonary diseases.

Authors

  • Zhenyu Cao
    Department of Radiology, Tongde Hospital of Zhejiang Province Afflicted to Zhejiang Chinese Medical University (Tongde Hospital of Zhejiang Province), Hangzhou, China.
  • Gang Xu
    University Hospitals of Leicester NHS Trust; UK.
  • Yuan Gao
    Engineering Research Center of EMR and Intelligent Expert System, Ministry of Education, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou Zhejiang Province, China.
  • Jianying Xu
    Department of Radiology, Tongde Hospital of Zhejiang Province Afflicted to Zhejiang Chinese Medical University (Tongde Hospital of Zhejiang Province), Hangzhou, China.
  • Fengjuan Tian
    Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Hengfeng Shi
    Department of Radiology, Anqing Municipal Hospital, Anqing, Anhui, China.
  • Dengfa Yang
    Department of Radiology, Taizhou Municipal Hospital, Taizhou, China.
  • Zongyu Xie
    The First Affiliated Hospital of Bengbu Medical College, No. 287 Changhuai Road, Bengbu Anhui, 233004, China. zongyuxie@sina.com.
  • Jian Wang
    Veterinary Diagnostic Center, Shanghai Animal Disease Control Center, Shanghai, China.

Keywords

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