Deep learning system compared with expert endoscopists in predicting early gastric cancer and its invasion depth and differentiation status (with videos).

Journal: Gastrointestinal endoscopy
Published Date: Jul 7, 2021

Abstract

BACKGROUND AND AIMS: We aimed to develop and validate a deep learning-based system that covers various aspects of early gastric cancer (EGC) diagnosis, including detecting gastric neoplasm, identifying EGC, and predicting EGC invasion depth and differentiation status. Herein, we provide a state-of-the-art comparison of the system with endoscopists using real-time videos in a nationwide human-machine competition.

Authors

  • Lianlian Wu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Jing Wang
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Xinqi He
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
  • Yijie Zhu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
  • Xiaoda Jiang
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
  • Yiyun Chen
    School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China; State Key Laboratory of Soil and Sustainable Agriculture, Chinese Academy of Sciences, Nanjing 210008, China. Electronic address: chenyy@whu.edu.cn.
  • Yonggui Wang
    Hubei Key Laboratory of Critical Zone Evolution, School of Geography and Information Engineering, China University of Geosciences, Wuhan, China.
  • Li Huang
    National Research Center for Resettlement (NRCR), Hohai University, 1 Xikang Road, Nanjing 210098, China. lily8214@hhu.edu.cn.
  • Renduo Shang
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
  • Zehua Dong
    Department of Internal Medicine, Renmin Hospital of Wuhan University, 99 Zhangzhidong Road, Wuhan, 430060, Hubei Province, China.
  • Boru Chen
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
  • Xiao Tao
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China; Key Laboratory of Hubei Province for Digestive System Disease, Renmin Hospital of Wuhan University, Wuhan, China; Hubei Provincial Clinical Research Center for Digestive Disease Minimally Invasive Incision, Renmin Hospital of Wuhan University, Wuhan, China.
  • Qi Wu
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Honggang Yu
    Department of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.

Keywords

External Resources

Popular Topics
Recent Journals