Development and multicenter validation of chest X-ray radiography interpretations based on natural language processing.

Journal: Communications medicine
Published Date: Oct 28, 2021

Abstract

BACKGROUND: Artificial intelligence can assist in interpreting chest X-ray radiography (CXR) data, but large datasets require efficient image annotation. The purpose of this study is to extract CXR labels from diagnostic reports based on natural language processing, train convolutional neural networks (CNNs), and evaluate the classification performance of CNN using CXR data from multiple centers.

Authors

  • Yaping Zhang
    Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080 China.
  • Mingqian Liu
    Winning Health Technology Ltd., Shouyang Rd., Lane 99, No. 9, Shanghai, 200072 China.
  • Shundong Hu
    Radiology Department, Shanghai Sixth People Hospital, Shanghai Jiao Tong University School of Medicine, Yishan Rd. 600, Shanghai, 200233 China.
  • Yao Shen
    Department of Computer Science and Engineering, Shanghai Jiao Tong University, Dongchuan Rd. 800, Shanghai, 200240 China.
  • Jun Lan
    Winning Health Technology Ltd., Shouyang Rd., Lane 99, No. 9, Shanghai, 200072 China.
  • Beibei Jiang
    Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080 China.
  • Geertruida H de Bock
    University of Groningen, University Medical Center Groningen, Department of Epidemiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Rozemarijn Vliegenthart
    University of Groningen, University Medical Center Groningen, Department of Radiology, Hanzeplein 1, 9713 GZ Groningen, The Netherlands.
  • Xu Chen
    School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.
  • Xueqian Xie
    Radiology Department, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Haining Rd.100, Shanghai, 200080 China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals