T
Tomohiro Tada
Researcher at University of Tokyo
Publications - 85
Citations - 3164
Tomohiro Tada is an academic researcher from University of Tokyo. The author has contributed to research in topics: Medicine & Convolutional neural network. The author has an hindex of 23, co-authored 74 publications receiving 1896 citations.
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Journal ArticleDOI
Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.
Toshiaki Hirasawa,Kazuharu Aoyama,Tetsuya Tanimoto,Soichiro Ishihara,Satoki Shichijo,Tsuyoshi Ozawa,Tatsuya Ohnishi,Mitsuhiro Fujishiro,Keigo Matsuo,Junko Fujisaki,Tomohiro Tada +10 more
TL;DR: The constructed CNN system for detecting gastric cancer could process numerous stored endoscopic images in a very short time with a clinically relevant diagnostic ability and may be well applicable to daily clinical practice to reduce the burden of endoscopists.
Journal ArticleDOI
Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks
Yoshimasa Horie,Toshiyuki Yoshio,Kazuharu Aoyama,Shoichi Yoshimizu,Yusuke Horiuchi,Akiyoshi Ishiyama,Toshiaki Hirasawa,Tomohiro Tsuchida,Tsuyoshi Ozawa,Soichiro Ishihara,Youichi Kumagai,Mitsuhiro Fujishiro,Iruru Maetani,Junko Fujisaki,Tomohiro Tada +14 more
TL;DR: The constructed CNN system for detecting esophageal cancer can analyze stored endoscopic images in a short time with high sensitivity, however, more training would lead to higher diagnostic accuracy.
Journal ArticleDOI
Application of Convolutional Neural Networks in the Diagnosis of Helicobacter pylori Infection Based on Endoscopic Images.
Satoki Shichijo,Shuhei Nomura,Kazuharu Aoyama,Yoshitaka Nishikawa,Motoi Miura,Takahide Shinagawa,Hirotoshi Takiyama,Tetsuya Tanimoto,Soichiro Ishihara,Keigo Matsuo,Tomohiro Tada +10 more
TL;DR: H. pylori gastritis could be diagnosed based on endoscopic images using CNN with higher accuracy and in a considerably shorter time compared to manual diagnosis by endoscopists.
Journal ArticleDOI
Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network.
Tomonori Aoki,Atsuo Yamada,Kazuharu Aoyama,Hiroaki Saito,Akiyoshi Tsuboi,Ayako Nakada,Ryota Niikura,Mitsuhiro Fujishiro,Shiro Oka,Soichiro Ishihara,Tomoki Matsuda,Shinji Tanaka,Kazuhiko Koike,Tomohiro Tada +13 more
TL;DR: A new system based on CNN to automatically detect erosions and ulcerations in WCE images is developed and validated and may be a crucial step in the development of daily-use diagnostic software for W CE images to help reduce oversights and the burden on physicians.
Journal ArticleDOI
Novel computer-assisted diagnosis system for endoscopic disease activity in patients with ulcerative colitis.
Tsuyoshi Ozawa,Soichiro Ishihara,Soichiro Ishihara,Mitsuhiro Fujishiro,Hiroaki Saito,Youichi Kumagai,Satoki Shichijo,Kazuharu Aoyama,Tomohiro Tada +8 more
TL;DR: The performance of the CNN-based CAD system was robust when used to identify endoscopic inflammation severity in patients with UC, highlighting its promising role in supporting less-experienced endoscopists and reducing interobserver variability.