Upper endoscopy photodocumentation quality evaluation with novel deep learning system.

Journal: Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Published Date: Dec 1, 2021

Abstract

OBJECTIVES: Visualization and photodocumentation during endoscopy procedures are suggested to be one indicator for endoscopy performance quality. However, this indicator is difficult to measure and audit manually in clinical practice. Artificial intelligence (AI) is an emerging technology that may solve this problem.

Authors

  • Yuan-Yen Chang
    Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan.
  • Hsu-Heng Yen
    Artificial Intelligence Development Center, Changhua Christian Hospital, Changhua, Taiwan. 91646@cch.org.tw.
  • 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.
  • Chia Wei Yang
    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.

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