Interpretable and generalizable deep learning model for preoperative assessment of microvascular invasion and outcome in hepatocellular carcinoma based on MRI: a multicenter study.

Abstract

Authors

• Xue Dong
  Division of Plastic and Reconstructive Surgery, Weill Cornell Medicine, New York, NY, United States of America.
• Xibin Jia
  Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China.
• Wei Zhang
  The First Affiliated Hospital of Nanchang University, Nanchang, China.
• Jingxuan Zhang
  Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.
• Hui Xu
  No 202 Hospital of People's Liberation Army, Liaoning 110003, China.
• Lixue Xu
  Department of Radiology, Beijing Friendship Hospital, Capital Medical University, No. 95 YongAn Road, Beijing, 100050, People's Republic of China.
• Caili Ma
  Clinical Nursing Teaching and Research Section, The Second Xiangya Hospital of Central South University, Changsha, PR China. Electronic address: macaili@csu.edu.cn.
• Hongjie Hu
• Jiawen Luo
• Jingfeng Zhang
  Department of Radiology, Ningbo No. 2 Hospital, Ningbo, 315010, China (J.Z.).
• Zhenchang Wang
  School of Biological Science and Medical Engineering, Beihang University, Beijing, China.
• Wenbin Ji
  Department of Radiology, Taizhou Hospital, Zhejiang University, Taizhou, Zhejiang, China.
• Dawei Yang
  Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital Fudan University, Shanghai, China.
• Zhenghan Yang
  Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.

Keywords

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