Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow‐band …
H Ueyama, Y Kato, Y Akazawa… - Journal of …, 2021 - Wiley Online Library
Abstract 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 …
has made a huge contribution to clinical practice. However, acquiring skill at ME‐NBI …
Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band …
H Ueyama, Y Kato, Y Akazawa, N Yatagai… - Journal of …, 2020 - europepmc.org
Methods The AI-assisted CNN-CAD system (ResNet50) was trained and validated on a
dataset of 5574 ME-NBI images (3797 EGCs, 1777 non-cancerous mucosa and lesions). To …
dataset of 5574 ME-NBI images (3797 EGCs, 1777 non-cancerous mucosa and lesions). To …
Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band …
H Ueyama, Y Kato, Y Akazawa… - Journal of …, 2021 - pubmed.ncbi.nlm.nih.gov
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 …
a huge contribution to clinical practice. However, acquiring skill at ME-NBI diagnosis of early …
[HTML][HTML] Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow …
H Ueyama, Y Kato, Y Akazawa, N Yatagai… - Journal of …, 2021 - ncbi.nlm.nih.gov
Methods The AI‐assisted CNN‐CAD system (ResNet50) was trained and validated on a
dataset of 5574 ME‐NBI images (3797 EGCs, 1777 non‐cancerous mucosa and lesions) …
dataset of 5574 ME‐NBI images (3797 EGCs, 1777 non‐cancerous mucosa and lesions) …
Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow‐band …
H Ueyama, Y Kato, Y Akazawa, N Yatagai… - Journal of …, 2020 - cir.nii.ac.jp
抄録< jats: title> Abstract</jats: title>< jats: sec>< jats: title> Background and Aim</jats: title><
jats: p> Magnifying endoscopy with narrow‐band imaging (ME‐NBI) has made a huge …
jats: p> Magnifying endoscopy with narrow‐band imaging (ME‐NBI) has made a huge …
Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow‐band …
H Ueyama, Y Kato, Y Akazawa… - Journal of …, 2021 - search.ebscohost.com
Abstract 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 …
has made a huge contribution to clinical practice. However, acquiring skill at ME‐NBI …
Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band …
H Ueyama, Y Kato, Y Akazawa, N Yatagai… - Journal of …, 2020 - europepmc.org
Methods The AI-assisted CNN-CAD system (ResNet50) was trained and validated on a
dataset of 5574 ME-NBI images (3797 EGCs, 1777 non-cancerous mucosa and lesions). To …
dataset of 5574 ME-NBI images (3797 EGCs, 1777 non-cancerous mucosa and lesions). To …