Application of machine learning in the diagnosis of gastric cancer based on noninvasive characteristics.

Journal: PloS one
PMID: 33382829

Abstract

BACKGROUND: The diagnosis of gastric cancer mainly relies on endoscopy, which is invasive and costly. The aim of this study is to develop a predictive model for the diagnosis of gastric cancer based on noninvasive characteristics.

Authors

  • Shuang-Li Zhu
    Department of Geriatric VIP NO.1, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang Province, China.
  • Jie Dong
    Department of Urology, Eastern Theater Command General Hospital, Nanjing，Jiangsu 210002, Chinia.
  • Chenjing Zhang
    Department of Gastroenterology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang Province, China.
  • Yao-Bo Huang
    Department of Financial Security, Alibaba Group, Hangzhou, Zhejiang Province, China.
  • Wensheng Pan
    Department of Gastroenterology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, Zhejiang Province, China.

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