Using machine-learning algorithms to identify patients at high risk of upper gastrointestinal lesions for endoscopy.

Journal: Journal of gastroenterology and hepatology
Published Date: Oct 1, 2021

Abstract

BACKGROUND AND AIM: Endoscopic screening for early detection of upper gastrointestinal (UGI) lesions is important. However, population-based endoscopic screening is difficult to implement in populous countries. By identifying high-risk individuals from the general population, the screening targets can be narrowed to individuals who are in most need of an endoscopy. This study was designed to develop an artificial intelligence (AI)-based model to predict patient risk of UGI lesions to identify high-risk individuals for endoscopy.

Authors

  • Yongjia Liu
    Department of Gastroenterology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
  • Da Lin
    Department of Gastroenterology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
  • Lan Li
    Department of Otolaryngology, Shenzhen Children's Hospital, Shenzhen, China.
  • Yu Chen
    State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, China.
  • Jiayao Wen
    Department of Gastroenterology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
  • Yiguang Lin
    School of Life Sciences, University of Technology Sydney, Sydney, Australia. Electronic address: Yiguang.lin@uts.edu.au.
  • Xingxiang He
    Department of Gastroenterology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.

Keywords

External Resources

Popular Topics
Recent Journals