An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video).

Journal: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Published Date: Jul 2, 2024

Abstract

BACKGROUND: Accurate prediction of pathologic results for early gastric cancer (EGC) based on endoscopic findings is essential in deciding between endoscopic and surgical resection. This study aimed to develop an artificial intelligence (AI) model to assess comprehensive pathologic characteristics of EGC using white-light endoscopic images and videos.

Authors

  • Seunghan Lee
    Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.
  • Jiwoon Jeon
    Ainex Corporation, Seoul, Republic of Korea.
  • Jinbae Park
    Ainex Corporation, Seoul, Republic of Korea.
  • Young Hoon Chang
    Department of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam-Si, Gyeonggi-Do, Republic of Korea.
  • Cheol Min Shin
    Department of Internal Medicine, Seoul National University Bundang Hospital, Seoungnam-Si, Gyeonggi-Do, Republic of Korea.
  • Mi Jin Oh
    Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.
  • Su Hyun Kim
    Center for Health Promotion and Optimal Aging, Seoul National University Hospital, Seoul, Republic of Korea.
  • Seungkyung Kang
    Center for Health Promotion and Optimal Aging, Seoul National University Hospital, Seoul, Republic of Korea.
  • Su Hee Park
    Center for Health Promotion and Optimal Aging, Seoul National University Hospital, Seoul, Republic of Korea.
  • Sang Gyun Kim
    Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
  • Hyuk-Joon Lee
  • Han-Kwang Yang
  • Hey Seung Lee
    Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Soo-Jeong Cho
    Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, Seoul, Korea.

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