Convolutional capsnet: A novel artificial neural network approach to detect COVID-19 disease from X-ray images using capsule networks
Detection Principle
Imaging-X-ray
Target
x-rays images
Testing Method Category
In_silico
Testing Method
deep learning models
Testing Method - Additional Info
a novel artificial neural network, Convolutional CapsNet for the detection of COVID-19 disease is proposed by using chest X-ray images with capsule networks. The proposed approach is designed to provide fast and accurate diagnostics for COVID-19 diseases with binary classification (COVID-19, and No-Findings), and multi-class classification (COVID-19, and No-Findings, and Pneumonia).
Reported Performance
accuracy: 97.24%(binary class); 84.22% (multi-class)
Sample Size
1420 x-ray
Peer-reviewed
yes
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