Kudo Shin-Ei, Mori Yuichi, Abdel-Aal Usama M, Misawa Masashi, Itoh Hayato, Oda Masahiro, Mori Kensaku
Digestive Disease Center, Showa University Northern Yokohama Hospital, Yokohama, Japan.
Internal Medicine, Faculty of Medicine, Sohag University, Sohag, Egypt.
Transl Gastroenterol Hepatol. 2021 Oct 25;6:64. doi: 10.21037/tgh.2019.12.14. eCollection 2021.
Computer-aided diagnosis (CAD) for colonoscopy with use of artificial intelligence (AI) is catching increased attention of endoscopists. CAD allows automated detection and pathological prediction, namely optical biopsy, of colorectal polyps during real-time endoscopy, which help endoscopists avoid missing and/or misdiagnosing colorectal lesions. With the increased number of publications in this field and emergence of the AI medical device that have already secured regulatory approval, CAD in colonoscopy is now being implemented into clinical practice. On the other side, drawbacks and weak points of CAD in colonoscopy have not been thoroughly discussed. In this review, we provide an overview of CAD for optical biopsy of colorectal lesions with a particular focus on its clinical applications and limitations.
利用人工智能（AI）的结肠镜检查计算机辅助诊断（CAD）正越来越受到内镜医师的关注。CAD能够在实时内镜检查期间对大肠息肉进行自动检测和病理预测，即光学活检，这有助于内镜医师避免漏诊和/或误诊大肠病变。随着该领域出版物数量的增加以及已获得监管批准的AI医疗设备的出现，结肠镜检查的CAD目前正在临床实践中得到应用。另一方面，结肠镜检查CAD的缺点和弱点尚未得到充分讨论。在本综述中，我们概述了用于大肠病变光学活检的CAD，特别关注其临床应用和局限性。
