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10.1016/j.compbiomed.2021.104306 http://scihub22266oqcxt.onion/10.1016/j.compbiomed.2021.104306 33780867!7943389!33780867     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Comput+Biol+Med 2021 ; 132 (ä): 104306 Nephropedia Template TP {{tp|p=33780867|t=2021. Deep learning for diagnosis of COVID-19 using 3D CT scans |pdf=|usr=}}{{33780867}} gab.com Text Deep learning for diagnosis of COVID-19 using 3D CT scans JO: Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=33780867 #FOAvip A new pneumonia-type coronavirus, COVID-19, recently emerged in Wuhan, China. COVID-19 has subsequently infected many people and caused many deaths worldwide. Isolating infected people is one of the methods of preventing the spread of this virus. CT scans provide detailed imaging of the lungs and assist radiologists in diagnosing COVID-19 in hospitals. However, a person's CT scan contains hundreds of slides, and the diagnosis of COVID-19 using such scans can lead to delays in hospitals. Artificial intelligence techniques could assist radiologists with rapidly and accurately detecting COVID-19 infection from these scans. This paper proposes an artificial intelligence (AI) approach to classify COVID-19 and normal CT volumes. The proposed AI method uses the ResNet-50 deep learning model to predict COVID-19 on each CT image of a 3D CT scan. Then, this AI method fuses image-level predictions to diagnose COVID-19 on a 3D CT volume. We show that the proposed deep learning model provides 96% AUC value for detecting COVID-19 on CT scans. Twit Text FOAVip Deep learning for diagnosis of COVID-19 using 3D CT scans ????Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=33780867 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33780867 #FOAvip English Wikipedia <ref>{{Cite pmid|33780867}}</ref> Deep learning for diagnosis of COVID-19 using 3D CT scans #MMPMID33780867 Serte S; Demirel H Comput Biol Med 2021[May]; 132 (ä): 104306 PMID33780867show ga A new pneumonia-type coronavirus, COVID-19, recently emerged in Wuhan, China. COVID-19 has subsequently infected many people and caused many deaths worldwide. Isolating infected people is one of the methods of preventing the spread of this virus. CT scans provide detailed imaging of the lungs and assist radiologists in diagnosing COVID-19 in hospitals. However, a person's CT scan contains hundreds of slides, and the diagnosis of COVID-19 using such scans can lead to delays in hospitals. Artificial intelligence techniques could assist radiologists with rapidly and accurately detecting COVID-19 infection from these scans. This paper proposes an artificial intelligence (AI) approach to classify COVID-19 and normal CT volumes. The proposed AI method uses the ResNet-50 deep learning model to predict COVID-19 on each CT image of a 3D CT scan. Then, this AI method fuses image-level predictions to diagnose COVID-19 on a 3D CT volume. We show that the proposed deep learning model provides 96% AUC value for detecting COVID-19 on CT scans. |*COVID-19[MESH] |*Deep Learning[MESH] |Artificial Intelligence[MESH] |China[MESH] |Humans[MESH] |SARS-CoV-2[MESH]Deep learning for diagnosis of COVID-19 using 3D CT scans (epmc).pdf DeepDyve Pubget Overpricing