Duodenal papilla radiomics-based prediction model for post-ERCP pancreatitis using machine learning: a retrospective multicohort study.

Journal: Gastrointestinal endoscopy
PMID: 38583542

Abstract

BACKGROUND AND AIMS: The duodenal papillae are the primary and essential pathway for ERCP, greatly determining its complexity and outcome. We investigated the association between papilla morphology and post-ERCP pancreatitis (PEP) and constructed a robust model for PEP prediction.

Authors

  • Kangjie Chen
    Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Haihao Lin
    School of Mathematical Sciences, Zhejiang University, Hangzhou, China.
  • Feiyi Zhang
    Polytechnic Institute, Zhejiang University, Hangzhou, China.
  • Ziying Chen
    Polytechnic Institute, Zhejiang University, Hangzhou, China.
  • Huajie Ying
    Department of Hepatobiliary and Pancreatic Surgery, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Linping Cao
    Department of Hepatobiliary and Pancreatic Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China. Electronic address: caolinping510@zju.edu.cn.
  • Jianfeng Fang
    Division of Hepatobiliary Pancreatic Surgery, Department of Surgery, Shaoxing People's Hospital, Shaoxing, China.
  • Danyang Zhu
    Division of Oncological Surgery, Department of Surgery, Haining Hospital of Traditional Chinese Medicine, Haining Cancer Hospital, Haining, China.
  • Kewei Liang
    National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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