Nature Communications (Feb 2021)
Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images
- Wenying Zhou,
- Yang Yang,
- Cheng Yu,
- Juxian Liu,
- Xingxing Duan,
- Zongjie Weng,
- Dan Chen,
- Qianhong Liang,
- Qin Fang,
- Jiaojiao Zhou,
- Hao Ju,
- Zhenhua Luo,
- Weihao Guo,
- Xiaoyan Ma,
- Xiaoyan Xie,
- Ruixuan Wang,
- Luyao Zhou
Affiliations
- Wenying Zhou
- Department of Medical Ultrasonics, Institute for Diagnostic and Interventional Ultrasound, The First Affiliated Hospital, Sun Yat-sen University
- Yang Yang
- School of Computer Science and Engineering, Sun Yat-sen University
- Cheng Yu
- Department of Ultrasound, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
- Juxian Liu
- Department of Ultrasound, West China Hospital, Sichuan University
- Xingxing Duan
- Department of Ultrasound, Hunan Children’s Hospital
- Zongjie Weng
- Department of Medical Ultrasonics, Fujian Provincial Maternity and Children’s Hospital, Affiliated Hospital of Fujian Medical University
- Dan Chen
- Department of Ultrasound, Guangdong Women and Children’ Hospital
- Qianhong Liang
- Department of Ultrasound, Hexian Memorial Affiliated Hospital of Southern Medical University
- Qin Fang
- Department of Ultrasound, The First People’s Hospital of Foshan
- Jiaojiao Zhou
- Department of Ultrasound, West China Hospital, Sichuan University
- Hao Ju
- Department of Ultrasound, Shengjing Hospital of China Medical University
- Zhenhua Luo
- Institute of Precision Medicine, The First Affiliated Hospital, Sun Yat-sen University
- Weihao Guo
- Department of Medical Ultrasonics, Institute for Diagnostic and Interventional Ultrasound, The First Affiliated Hospital, Sun Yat-sen University
- Xiaoyan Ma
- Department of Ultrasound, Guangdong Women and Children’ Hospital
- Xiaoyan Xie
- Department of Medical Ultrasonics, Institute for Diagnostic and Interventional Ultrasound, The First Affiliated Hospital, Sun Yat-sen University
- Ruixuan Wang
- School of Computer Science and Engineering, Sun Yat-sen University
- Luyao Zhou
- Department of Medical Ultrasonics, Institute for Diagnostic and Interventional Ultrasound, The First Affiliated Hospital, Sun Yat-sen University
- DOI
- https://doi.org/10.1038/s41467-021-21466-z
- Journal volume & issue
-
Vol. 12,
no. 1
pp. 1 – 14
Abstract
It is still challenging to make accurate diagnosis of biliary atresia (BA) with sonographic gallbladder images particularly in rural areas without relevant expertise. Here, the authors develop a diagnostic deep learning model which favourable performance in comparison with human experts in multi-center external validation.
