A web-based tool for predicting gastric ulcers in Chinese elderly adults based on machine learning algorithms and noninvasive predictors: A national cross-sectional and cohort study.

Abstract

Authors

• Xingjian Xiao
  School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
• Xiaohan Yi
  , Beijing, China.
• Zumin Shi
  Discipline of Medicine, School of Medicine, Faculty of Health Sciences, University of Adelaide, Adelaide, Australia.
• Zongyuan Ge
  AIM for Health Lab, Faculty of IT, Monash University, Clayton, Victoria, Australia; Monash-Airdoc Research Lab, Faculty of IT, Monash University, Clayton, Victoria, Australia.
• Hualing Song
  School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China. Electronic address: 99shl@163.com.
• Hailei Zhao
  School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China. Electronic address: Zhao.hailei@shutcm.edu.cn.
• Tiantian Liang
  School of Electrical Engineering, Dalian Jiaotong University, 794 Huanghe Road, Dalian, 116028, China.
• Xinming Yang
  School of Public Health, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
• Suxian Liu
  Endoscopy Center, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
• Bo Sun
  College of Information Science and Technology, Beijing Normal University, Beijing, 100875, China. Electronic address: tosunbo@bnu.edu.cn.
• Xianglong Xu
  Artificial Intelligence and Modelling in Epidemiology Program, Melbourne Sexual Health Centre, Alfred Health, Melbourne, Australia.

Keywords

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