Development and validation of a deep learning-based algorithm for colonoscopy quality assessment.

Journal: Surgical endoscopy
Published Date: Sep 1, 2022

Abstract

BACKGROUND: Quality indicators should be assessed and monitored to improve colonoscopy quality in clinical practice. Endoscopists must enter relevant information in the endoscopy reporting system to facilitate data collection, which may be inaccurate. The current study aimed to develop a full deep learning-based algorithm to identify and analyze intra-procedural colonoscopy quality indicators based on endoscopy images obtained during the procedure.

Authors

  • Yuan-Yen Chang
    Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
  • Pai-Chi Li
    Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
  • Ruey-Feng Chang
    Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 10617, Taiwan and Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan.
  • Yu-Yao Chang
    Department of Colorectal Surgery, Changhua Christian Hospital, Changhua, Taiwan.
  • Siou-Ping Huang
    Division of Gastroenterology, Changhua Christian Hospital, Changhua, Taiwan.
  • Yang-Yuan Chen
    Division of Gastroenterology, Changhua Christian Hospital, Changhua, Taiwan.
  • Wen-Yen Chang
    Department of Medical Education, National Taiwan University Hospital, Taipei, Taiwan.
  • Hsu-Heng Yen
    Artificial Intelligence Development Center, Changhua Christian Hospital, Changhua, Taiwan. 91646@cch.org.tw.

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