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10.1007/s40009-020-01009-8 http://scihub22266oqcxt.onion/10.1007/s40009-020-01009-8 32836613!7391230!32836613     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Natl+Acad+Sci+Lett 2021 ; 44 (4): 347-350 Nephropedia Template TP {{tp|p=32836613|t=2021. Non-Invasive Technique-Based Novel Corona(COVID-19) Virus Detection Using CNN |pdf=|usr=}}{{32836613}} gab.com Text Non-Invasive Technique-Based Novel Corona(COVID-19) Virus Detection Using CNN JO: Natl Acad Sci Lett http://www.kidney.de/pget.php?&tw=1&pmid=32836613 #FOAvip A novel human coronavirus 2 (SARS-CoV-2) is an extremely acute respiratory syndrome which was reported in Wuhan, China in the later half 2019. Most of its primary epidemiological aspects are not appropriately known, which has a direct effect on monitoring, practices and controls. The main objective of this work is to propose a high speed, accurate and highly sensitive CT scan approach for diagnosis of COVID19. The CT scan images display several small patches of shadows and interstitial shifts, particularly in the lung periphery. The proposed method utilizes the ResNet architecture Convolution Neural Network for training the images provided by the CT scan to diagnose the coronavirus-affected patients effectively. By comparing the testing images with the training images, the affected patient is identified accurately. The accuracy and specificity are obtained 95.09% and 81.89%, respectively, on the sample dataset based on CT images without the inclusion of another set of data such as geographical location, population density, etc. Also, the sensitivity is obtained 100% in this method. Based on the results, it is evident that the COVID-19 positive patients can be classified perfectly by using the proposed method. Twit Text FOAVip Non-Invasive Technique-Based Novel Corona(COVID-19) Virus Detection Using CNN ????Natl Acad Sci Lett http://www.kidney.de/pget.php?&tw=1&pmid=32836613 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32836613 #FOAvip English Wikipedia <ref>{{Cite pmid|32836613}}</ref> Non-Invasive Technique-Based Novel Corona(COVID-19) Virus Detection Using CNN #MMPMID32836613 Raajan NR; Lakshmi VSR; Prabaharan N Natl Acad Sci Lett 2021[]; 44 (4): 347-350 PMID32836613show ga A novel human coronavirus 2 (SARS-CoV-2) is an extremely acute respiratory syndrome which was reported in Wuhan, China in the later half 2019. Most of its primary epidemiological aspects are not appropriately known, which has a direct effect on monitoring, practices and controls. The main objective of this work is to propose a high speed, accurate and highly sensitive CT scan approach for diagnosis of COVID19. The CT scan images display several small patches of shadows and interstitial shifts, particularly in the lung periphery. The proposed method utilizes the ResNet architecture Convolution Neural Network for training the images provided by the CT scan to diagnose the coronavirus-affected patients effectively. By comparing the testing images with the training images, the affected patient is identified accurately. The accuracy and specificity are obtained 95.09% and 81.89%, respectively, on the sample dataset based on CT images without the inclusion of another set of data such as geographical location, population density, etc. Also, the sensitivity is obtained 100% in this method. Based on the results, it is evident that the COVID-19 positive patients can be classified perfectly by using the proposed method. äNon-Invasive Technique-Based Novel Corona(COVID-19) Virus Detection Us(epmc).pdf DeepDyve Pubget Overpricing