Development and application of deep learning-based diagnostics for pathologic diagnosis of gastric endoscopic submucosal dissection specimens.

Journal: Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
Published Date: Apr 15, 2025

Abstract

BACKGROUND: Accurate diagnosis of ESD specimens is crucial for managing early gastric cancer. Identifying tumor areas in serially sectioned ESD specimens requires experience and is time-consuming. This study aimed to develop and evaluate a deep learning model for diagnosing ESD specimens.

Authors

  • Soomin Ahn
    Department of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Gyeonggi, 13620, Korea.
  • Yiyu Hong
  • Sujin Park
    Quality Evaluation Team, Samsung Bioepis Co., Ltd, Incheon, Republic of Korea.
  • Yunjoo Cho
    Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
  • Inwoo Hwang
    Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
  • Ji Min Na
    Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
  • Hyuk Lee
    Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Byung-Hoon Min
    Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, South Korea.
  • Jun Haeng Lee
    Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, South Korea.
  • Jae J Kim
    Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, South Korea.
  • Kyoung-Mee Kim
    The Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. kkmkys@skku.edu.

Keywords

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