Automated machine learning model for predicting anastomotic strictures after esophageal cancer surgery: a retrospective cohort study.

Journal: Surgical endoscopy
Published Date: Jun 1, 2025

Abstract

BACKGROUND: Anastomotic strictures (AS) frequently occurs in patients following esophageal cancer surgery, significantly affecting their long-term quality of life. This study aims to develop a machine learning model to predict high-risk AS, enabling early intervention and precise management.

Authors

  • Junxi Hu
    College of Clinical Medicine, Yangzhou University, Yangzhou, China.
  • Qingwen Liu
    Department of Thoracic Surgery, Northern Jiangsu People's Hospital, Yangzhou, 225001, China.
  • Wenbo He
  • Jun Wu
    Department of Emergency, Zhuhai Integrated Traditional Chinese and Western Medicine Hospital, Zhuhai, 519020, Guangdong Province, China. quanshabai43@163.com.
  • Dong Zhang
    Institute of Acoustics, Nanjing University, Nanjing 210093, China.
  • Chao Sun
    Hospital for Skin Diseases and Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China.
  • Shichun Lu
    Clinical Medical College, Yangzhou University, Yangzhou, 225001, China.
  • Xiaolin Wang
    Department of Urology, Nantong Tumor Hospital, Nantong, Jiangsu, China.
  • Yusheng Shu
    College of Clinical Medicine, Yangzhou University, Yangzhou, China.

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