Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

Journal: Journal of digestive diseases
PMID: 40176375

Abstract

OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high-risk adenomas among colorectal polyps ≤ 10 mm with standard white-light endoscopy.

Authors

  • Da Yeon Ham
    Division of Gastroenterology, Department of Internal Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea.
  • Hyun Joo Jang
    Division of Gastroenterology, Department of Internal Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea.
  • Sea Hyub Kae
    Division of Gastroenterology, Department of Internal Medicine, Hallym University Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, Republic of Korea.
  • Chang Kyo Oh
    Division of Gastroenterology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
  • Sungjin Hong
    Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea.
  • Jae Gon Lee
    Department of Internal Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea.

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