A real-time interpretable artificial intelligence model for the cholangioscopic diagnosis of malignant biliary stricture (with videos).

Journal: Gastrointestinal endoscopy
PMID:

Abstract

BACKGROUND AND AIMS: It is crucial to accurately determine malignant biliary strictures (MBSs) for early curative treatment. This study aimed to develop a real-time interpretable artificial intelligence (AI) system to predict MBSs under digital single-operator cholangioscopy (DSOC).

Authors

  • Xiang Zhang
    Department of Orthopedics, Orthopedic Research Institute, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
  • Dehua Tang
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu 210008, China.
  • Jin-Dong Zhou
    National Institute of Healthcare Data Science at Nanjing University, Nanjing, Jiangsu, China; National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing, Jiangsu, China.
  • Muhan Ni
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu 210008, China.
  • Peng Yan
    Department of Interventional Neuroradiology, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Room 603, No. 6 Tiantan Xili, Dongcheng District, Beijing, China.
  • Zhenyu Zhang
    Laboratory of Industrial Biotechnology of Department of Education, Jiangnan University, Wuxi 214122, Jiangsu, China.
  • Tao Yu
    Department of Smart Experience Design Kookmin University, Seoul 02707, Republic of Korea.
  • Qiang Zhan
    Department of Gastroenterology, Wuxi People's Hospital, Affiliated Wuxi People's Hospital with Nanjing Medical University, Wuxi, Jiangsu 214023, China.
  • Yonghua Shen
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, China; Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
  • Lin Zhou
    Guangdong Province Key Laboratory for Biotechnology Drug Candidates, School of Biosciences and Biopharmaceutics, Guangdong Pharmaceutical University Guangzhou 510006 People's Republic of China zhoulin@gdpu.edu.cn +86-20-39352151 +86-20-39352151.
  • Ruhua Zheng
    Department of Gastroenterology, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, China; Department of Gastroenterology, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, China.
  • Xiaoping Zou
    Department of Gastroenterology, Nanjing Drum Tower Hospital of Nanjing University, Nanjing, China.
  • Bin Zhang
    Department of Psychiatry, Sleep Medicine Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Wu-Jun Li
    National Institute of Healthcare Data Science at Nanjing University, Nanjing, Jiangsu 210008, China; National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing, Jiangsu 210008, China; Center for Medical Big Data, Nanjing Drum Tower Hospital, Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing, Jiangsu 210008, China. Electronic address: liwujun@nju.edu.cn.
  • Lei Wang
    Department of Nursing, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.