Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.

Abstract

Authors

• Heling Bao
  Department of Maternal and Child Health, School of Public Health, Peking University, Beijing, China.
• Hui Bi
  Department of Obstetrics and Gynecology, Peking University First Hospital, Beijing, China.
• Xiaosong Zhang
  Data Mining Lab, University of Electronic Science and Technology of China, 611731 Chengdu, China; School of Computer Science and Engineering, University of Electronic Science and Technology of China, 611731 Chengdu, China.
• Yun Zhao
  The First Affiliated Hospital of Ningbo University, Ningbo, People's Republic of China.
• Yan Dong
• Xiping Luo
  Guangdong Maternal and Child Health Care Hospital, Guangzhou, China.
• Deping Zhou
  Chongqing Health Center for Women and Children, Chongqing, China.
• Zhixue You
  The First Affiliated Hospital With Nanjing Medical University, Nanjing, China.
• Yinglan Wu
  Hunan Provincial Maternal and Child Health Care Hospital, Changsha, China.
• Zhaoyang Liu
  Northwest Women and Children Hospital, Xi'an, China.
• Yuping Zhang
  School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China.
• Juan Liu
  Key State Laboratory of Software Engineering, School of Computer, Wuhan University, Wuhan 430072, PR China. Electronic address: liujuan@whu.edu.cn.
• Liwen Fang
  National Center for Chronic and Non-communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
• Linhong Wang
  Landing Cloud Medical Laboratory Co., Wuhan, China.

Keywords

External Resources