Artificial intelligence using a convolutional neural network for automatic detection of small‐bowel angioectasia in capsule endoscopy images-Reference-Cited by-同舟云学术

Artificial intelligence using a convolutional neural network for automatic detection of small‐bowel angioectasia in capsule endoscopy images

Published:2020-03 Issue:3 Volume:32 Page:382-390
ISSN:0915-5635
Container-title:Digestive Endoscopy
language:en
Short-container-title:Digestive Endoscopy

Author:

Tsuboi Akiyoshi¹,Oka Shiro¹^ORCID,Aoyama Kazuharu²,Saito Hiroaki³,Aoki Tomonori⁴,Yamada Atsuo⁴^ORCID,Matsuda Tomoki³,Fujishiro Mitsuhiro⁵,Ishihara Soichiro⁶⁷,Nakahori Masato³,Koike Kazuhiko⁴,Tanaka Shinji¹,Tada Tomohiro²⁶⁷

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 GastroenterologyTokyo 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

7. Tada Tomohiro Institute of Gastroenterology and Proctology Saitama Japan

Publisher

Wiley

Subject

Gastroenterology,Radiology Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/den.13507

Reference40 articles.

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4. Outcome of patients with obscure gastrointestinal bleeding after capsule endoscopy: Report of 100 consecutive cases

5. The role of wireless capsule endoscopy in investigating unexplained iron deficiency anemia after negative endoscopic evaluation of the upper and lower gastrointestinal tract

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