Artificial intelligence in pancreaticobiliary endoscopy: Current applications and future directions.

Journal: Journal of digestive diseases
PMID: 39740251

Abstract

Pancreaticobiliary endoscopy is an essential tool for diagnosing and treating pancreaticobiliary diseases. However, it does not fully meet clinical needs, which presents challenges such as significant difficulty in operation and risks of missed diagnosis or misdiagnosis. In recent years, artificial intelligence (AI) has enhanced the diagnostic and treatment efficiency and quality of pancreaticobiliary endoscopy. Diagnosis and differential diagnosis based on endoscopic ultrasound (EUS) images, pathology of EUS-guided fine-needle aspiration or biopsy, need for endoscopic retrograde cholangiopancreatography (ERCP) and assessment of operational difficulty, postoperative complications and prediction of patient prognosis, and real-time procedure guidance. This review provides an overview of AI applications in pancreaticobiliary endoscopy and proposes future development directions in aspects such as data quality and algorithmic interpretability, aiming to provide new insights for the integration of AI technology with pancreaticobiliary endoscopy.

Authors

  • Huan Jiang
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China (X.C., Q.Y., J.P., Z.H., Q.L., Y.N., F.L., H.J., K.X.).
  • Lian Song Ye
    Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.
  • Xiang Lei Yuan
    Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.
  • Qi Luo
    B-DAT & CICAEET, School of Information and Control, Nanjing University of Information Science and Technology, Nanjing 210044, PR China.
  • Nuo Ya Zhou
    Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China.
  • Bing Hu
    Department of Gastroenterology, West China Hospital, Sichuan University, Chengdu, China.

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