Constructing an artificial intelligence-assisted system for the assessment of gastroesophageal valve function based on the hill classification (with video).

Journal: BMC medical informatics and decision making
PMID: 40128700

Abstract

OBJECTIVE: In the functional assessment of the esophagogastric junction (EGJ), the endoscopic Hill classification plays a pivotal role in classifying the morphology of the gastroesophageal flap valve (GEFV). This study aims to develop an artificial intelligence model for Hill classification to assist endoscopists in diagnosis, covering the entire process from model development, testing, interpretability analysis, to multi-terminal deployment.

Authors

  • Jian Chen
    School of Pharmacy, Shanghai Jiaotong University, Shanghai, China.
  • Ganhong Wang
    Department of Gastroenterology, Changshu Traditional Chinese Medicine Hospital (New District Hospital), Suzhou, 215500, China.
  • Kaijian Xia
    Intelligent Medical Technology Research Center, Changshu Hospital Affiliated to Soochow University, Changshu, China.
  • Zhenni Wang
    Department of Electrical Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong Special Administrative Region of China. Electronic address: znwang3@cityu.edu.hk.
  • Luojie Liu
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, Suzhou, China.
  • Xiaodan Xu
    Department of Gastroenterology, Changshu Hospital Affiliated to Soochow University, First People's Hospital of Changshu City, No.1 Shuyuan Street, Changshu, Jiangsu, 215500, China. xuxiaodan20@126.com.

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