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Artificial intelligence using a convolutional neural network for automatic detection of small-bowel angioectasia in capsule endoscopy images
Authors:Akiyoshi Tsuboi  Shiro Oka  Kazuharu Aoyama  Hiroaki Saito  Tomonori Aoki  Atsuo Yamada  Tomoki Matsuda  Mitsuhiro Fujishiro  Soichiro Ishihara  Masato Nakahori  Kazuhiko Koike  Shinji Tanaka  Tomohiro Tada
Affiliation:1. Department of Endoscopy, Hiroshima University Hospital, Hiroshima, Japan;2. AI Medical Service Inc., Tokyo, Japan;3. Department of Gastroenterology, Sendai Kousei Hospital, Miyagi, Japan;4. Department of Gastroenterology, Tokyo, Japan;5. Department of Gastroenterology & Hepatology, Nagoya University Graduate School of Medicine, Aichi, Japan;6. Department of Surgical Oncology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan;7. AI Medical Service Inc., Tokyo, Japan

Department of Surgical Oncology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

Tada Tomohiro Institute of Gastroenterology and Proctology, Saitama, Japan

Abstract:
Keywords:angioectasia  capsule endoscopy  convolutional neural network  deep learning  small bowel
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