Is the diagnostic model based on convolutional neural network superior to pediatric radiologists in the ultrasonic diagnosis of biliary atresia?

Journal: Frontiers in medicine
Published Date: Jan 8, 2024

Abstract

BACKGROUND: Many screening and diagnostic methods are currently available for biliary atresia (BA), but the early and accurate diagnosis of BA remains a challenge with existing methods. This study aimed to use deep learning algorithms to intelligently analyze the ultrasound image data, build a BA ultrasound intelligent diagnostic model based on the convolutional neural network, and realize an intelligent diagnosis of BA.

Authors

  • Xingxing Duan
    Department of Ultrasound, Changsha Hospital for Maternal and Child Health Care, Changsha, China.
  • Liu Yang
    Department of Ultrasound, Hunan Children's Hospital, Changsha, China.
  • Weihong Zhu
    Department of Ultrasound, Chenzhou Children's Hospital, Chenzhou, China.
  • Hongxia Yuan
    Department of Ultrasound, Changsha Hospital for Maternal and Child Health Care, Changsha, China.
  • Xiangfen Xu
    Department of Ultrasound, Hunan Children's Hospital, Changsha, China.
  • Huan Wen
    Department of Ultrasound, Hunan Children's Hospital, Changsha, China.
  • Wengang Liu
    Department of Ultrasound, The Third Xiangya Hospital of Central South University, Changsha, China.
  • Meiyan Chen
    Department of Ultrasound, Chaling Hospital for Maternal and Child Health Care, Chaling, China.

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