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Cooperation Between Artificial Intelligence and Endoscopists for Diagnosing Invasion Depth of Early Gastric Cancer by Atsushi Goto; Naoto Kubota; Jun Nishikawa; Ryo Ogawa; Koichi Hamabe; Shinichi Hashimoto; Hiroyuki Ogihara; Yoshihiko Hamamoto; Hideo Yanai; Osamu Miura; Taro Takami is a Medicine article available to read on EtoBox.

What is Cooperation Between Artificial Intelligence and Endoscopists for Diagnosing Invasion Depth of Early Gastric Cancer about?

## Abstract ## Background and study aims The diagnostic ability of endoscopists to determine invasion depth of early gastric cancer is not favorable. We designed an artificial intelligence (AI) classifier for differentiating intramucosal and submucosal gastric cancers and examined it to establish a diagnostic method based on cooperation between AI and endoscopists. ## Patients and methods We prepared 500 training images using cases of mainly depressed-type early gastric cancer from 250 intramucosal cancers and 250 submucosal cancers. We also prepared 200 test images each of 100 cancers from another institution. We designed an AI classifier to differentiate between intramucosal and submucosal cancers by deep learning. We examined the performance of the AI classifier and the majority vote of the endoscopists as high confidence and low confidence diagnostic probability, respectively, and cooperatively combined them to establish a diagnostic method providing high accuracy. ## Results Internal evaluation of the training images showed that accuracy, sensitivity, specificity, and F1 measure by the AI classifier were 77%, 76%, 78%, and 0.768, and those of the majority vote of the endoscopi

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Author

Atsushi Goto; Naoto Kubota; Jun Nishikawa; Ryo Ogawa; Koichi Hamabe; Shinichi Hashimoto; Hiroyuki Ogihara; Yoshihiko Hamamoto; Hideo Yanai; Osamu Miura; Taro Takami

Publisher

Springer Science and Business Media LLC

Published

2022

Language

EN

Field

Medicine (Health Sciences)