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10.1016/j.compbiomed.2021.104399 http://scihub22266oqcxt.onion/10.1016/j.compbiomed.2021.104399 33892307!8049190!33892307     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Comput+Biol+Med 2021 ; 133 (ä): 104399 Nephropedia Template TP {{tp|p=33892307|t=2021. DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network |pdf=|usr=}}{{33892307}} gab.com Text DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network JO: Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=33892307 #FOAvip At present, the global pandemic as it relates to novel coronavirus pneumonia is still a very difficult situation. Due to the recent outbreak of novel coronavirus pneumonia, novel chest X-ray (CXR) images that can be used for deep learning analysis are very rare. To solve this problem, we propose a deep learning framework that integrates a convolutional neural network and a capsule network. DenseCapsNet, a new deep learning framework, is formed by the fusion of a dense convolutional network (DenseNet) and the capsule neural network (CapsNet), leveraging their respective advantages and reducing the dependence of convolutional neural networks on a large amount of data. Using 750 CXR images of lungs of healthy patients as well as those of patients with other pneumonia and novel coronavirus pneumonia, the method can obtain an accuracy of 90.7% and an F1 score of 90.9%, and the sensitivity for detecting COVID-19 can reach 96%. These results show that the deep fusion neural network DenseCapsNet has good performance in novel coronavirus pneumonia CXR radiography detection. Twit Text FOAVip DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network ????Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=33892307 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33892307 #FOAvip English Wikipedia <ref>{{Cite pmid|33892307}}</ref> DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network #MMPMID33892307 Quan H; Xu X; Zheng T; Li Z; Zhao M; Cui X Comput Biol Med 2021[Jun]; 133 (ä): 104399 PMID33892307show ga At present, the global pandemic as it relates to novel coronavirus pneumonia is still a very difficult situation. Due to the recent outbreak of novel coronavirus pneumonia, novel chest X-ray (CXR) images that can be used for deep learning analysis are very rare. To solve this problem, we propose a deep learning framework that integrates a convolutional neural network and a capsule network. DenseCapsNet, a new deep learning framework, is formed by the fusion of a dense convolutional network (DenseNet) and the capsule neural network (CapsNet), leveraging their respective advantages and reducing the dependence of convolutional neural networks on a large amount of data. Using 750 CXR images of lungs of healthy patients as well as those of patients with other pneumonia and novel coronavirus pneumonia, the method can obtain an accuracy of 90.7% and an F1 score of 90.9%, and the sensitivity for detecting COVID-19 can reach 96%. These results show that the deep fusion neural network DenseCapsNet has good performance in novel coronavirus pneumonia CXR radiography detection. |*COVID-19[MESH] |*Deep Learning[MESH] |Algorithms[MESH] |Humans[MESH] |Neural Networks, Computer[MESH] |SARS-CoV-2[MESH] |Tomography, X-Ray Computed[MESH]DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule (epmc).pdf DeepDyve Pubget Overpricing