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10.1007/s42979-020-00383-w http://scihub22266oqcxt.onion/10.1007/s42979-020-00383-w 33163975!7607889!33163975     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       SN+Comput+Sci 2020 ; 1 (6): 363 Nephropedia Template TP {{tp|p=33163975|t=2020. Deep Learning Applications to Combat Novel Coronavirus (COVID-19) Pandemic |pdf=|usr=}}{{33163975}} gab.com Text Deep Learning Applications to Combat Novel Coronavirus (COVID-19) Pandemic JO: SN Comput Sci http://www.kidney.de/pget.php?&tw=1&pmid=33163975 #FOAvip During this global pandemic, researchers around the world are trying to find out innovative technology for a smart healthcare system to combat coronavirus. The evidence of deep learning applications on the past epidemic inspires the experts by giving a new direction to control this outbreak. The aim of this paper is to discuss the contributions of deep learning at several scales including medical imaging, disease tracing, analysis of protein structure, drug discovery, and virus severity and infectivity to control the ongoing outbreak. A progressive search of the database related to the applications of deep learning was executed on COVID-19. Further, a comprehensive review is done using selective information by assessing the different perspectives of deep learning. This paper attempts to explore and discuss the overall applications of deep learning on multiple dimensions to control novel coronavirus (COVID-19). Though various studies are conducted using deep learning algorithms, there are still some constraints and challenges while applying for real-world problems. The ongoing progress in deep learning contributes to handle coronavirus infection and plays an effective role to develop appropriate solutions. It is expected that this paper would be a great help for the researchers who would like to contribute to the development of remedies for this current pandemic in this area. Twit Text FOAVip Deep Learning Applications to Combat Novel Coronavirus (COVID-19) Pandemic ????SN Comput Sci http://www.kidney.de/pget.php?&tw=1&pmid=33163975 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33163975 #FOAvip English Wikipedia <ref>{{Cite pmid|33163975}}</ref> Deep Learning Applications to Combat Novel Coronavirus (COVID-19) Pandemic #MMPMID33163975 Asraf A; Islam MZ; Haque MR; Islam MM SN Comput Sci 2020[]; 1 (6): 363 PMID33163975show ga During this global pandemic, researchers around the world are trying to find out innovative technology for a smart healthcare system to combat coronavirus. The evidence of deep learning applications on the past epidemic inspires the experts by giving a new direction to control this outbreak. The aim of this paper is to discuss the contributions of deep learning at several scales including medical imaging, disease tracing, analysis of protein structure, drug discovery, and virus severity and infectivity to control the ongoing outbreak. A progressive search of the database related to the applications of deep learning was executed on COVID-19. Further, a comprehensive review is done using selective information by assessing the different perspectives of deep learning. This paper attempts to explore and discuss the overall applications of deep learning on multiple dimensions to control novel coronavirus (COVID-19). Though various studies are conducted using deep learning algorithms, there are still some constraints and challenges while applying for real-world problems. The ongoing progress in deep learning contributes to handle coronavirus infection and plays an effective role to develop appropriate solutions. It is expected that this paper would be a great help for the researchers who would like to contribute to the development of remedies for this current pandemic in this area. äDeep Learning Applications to Combat Novel Coronavirus (COVID-19) Pand(epmc).pdf DeepDyve Pubget Overpricing