Development of artificial intelligence system for quality control of photo documentation in esophagogastroduodenoscopy.

Journal: Surgical endoscopy
Published Date: Jan 7, 2021

Abstract

BACKGROUND: Esophagogastroduodenoscopy (EGD) is generally a safe procedure, but adverse events often occur. This highlights the necessity of the quality control of EGD. Complete visualization and photo documentation of upper gastrointestinal (UGI) tracts are important measures in quality control of EGD. To evaluate these measures in large scale, we developed an AI-driven quality control system for EGD through convolutional neural networks (CNNs) using archived endoscopic images.

Authors

  • Seong Ji Choi
  • Mohammad Azam Khan
  • Hyuk Soon Choi
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
  • Jaegul Choo
  • Jae Min Lee
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
  • Soonwook Kwon
    Department of Anatomy, School of Medicine, Catholic University of Daegu, Daegu 42472, Republic of Korea.
  • Bora Keum
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.
  • Hoon Jai Chun
    Division of Gastroenterology and Hepatology, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea.

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