Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow‐band imaging-Reference-Cited by-同舟云学术

Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow‐band imaging

Published:2020-07-28 Issue:2 Volume:36 Page:482-489
ISSN:0815-9319
Container-title:Journal of Gastroenterology and Hepatology
language:en
Short-container-title:Journal of Gastroenterology and Hepatology

Author:

Ueyama Hiroya¹^ORCID,Kato Yusuke²,Akazawa Yoichi¹,Yatagai Noboru¹,Komori Hiroyuki¹,Takeda Tsutomu¹,Matsumoto Kohei¹,Ueda Kumiko¹,Matsumoto Kenshi¹,Hojo Mariko¹,Yao Takashi³,Nagahara Akihito¹,Tada Tomohiro²⁴

Affiliation:

1. Department of Gastroenterology Juntendo University School of Medicine Tokyo Japan

2. AI Medical Service Inc. Tokyo Japan

3. Department of Human Pathology Juntendo University School of Medicine Tokyo Japan

4. Tada Tomohiro Institute of Gastroenterology and Proctology Saitama Japan

Publisher

Wiley

Subject

Gastroenterology,Hepatology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jgh.15190

Reference33 articles.

1. Sensitivity of endoscopic screening for gastric cancer by the incidence method

2. Endoscopic Observation of Tissue by Narrowband Illumination

3. Magnifying endoscopy for diagnosing and delineating early gastric cancer

4. Novel Zoom Endoscopy Technique for Diagnosis of Small Flat Gastric Cancer: A Prospective, Blind Study

5. Magnifying endoscopy with narrow-band imaging achieves superior accuracy in the differential diagnosis of superficial gastric lesions identified with white-light endoscopy: a prospective study

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