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

Background and Aim Magnifying endoscopy with narrow‐band imaging (ME‐NBI) has made a huge contribution to clinical practice. However, acquiring skill at ME‐NBI diagnosis of early gastric cancer (EGC) requires considerable expertise and experience. Recently, artificial intelligence (AI), using deep l...

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Vydané v:	Journal of gastroenterology and hepatology Ročník 36; číslo 2; s. 482 - 489
Hlavní autori:	Ueyama, Hiroya, Kato, Yusuke, Akazawa, Yoichi, Yatagai, Noboru, Komori, Hiroyuki, Takeda, Tsutomu, Matsumoto, Kohei, Ueda, Kumiko, Matsumoto, Kenshi, Hojo, Mariko, Yao, Takashi, Nagahara, Akihito, Tada, Tomohiro
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Australia Wiley Subscription Services, Inc 01.02.2021 John Wiley and Sons Inc
Predmet:	Accuracy Artificial intelligence convolutional neural network Deep learning Diagnosis early gastric cancer Endoscopy Gastric cancer Gastritis Intestine magnifying endoscopy Mucosa narrow‐band imaging Neural networks Regular magnifying endoscopy convolutional neural network artificial intelligence narrow-band imaging early gastric cancer
ISSN:	0815-9319, 1440-1746, 1440-1746
On-line prístup:	Získať plný text
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