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10.1016/j.rinp.2021.104274 http://scihub22266oqcxt.onion/10.1016/j.rinp.2021.104274 33996399!8113008!33996399     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 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Results+Phys 2021 ; 25 (ä): 104274 Nephropedia Template TP {{tp|p=33996399|t=2021. Artificial neural networks and statistical models for optimization studying COVID-19 |pdf=|usr=}}{{33996399}} gab.com Text Artificial neural networks and statistical models for optimization studying COVID-19 JO: Results Phys http://www.kidney.de/pget.php?&tw=1&pmid=33996399 #FOAvip The biggest challenge facing the world in 2020 was the pandemic of the coronavirus disease (COVID-19). Since the start of 2020, COVID-19 has invaded the world, causing death to people and economic damage, which is cause for sadness and anxiety. Since the world has passed from the first peak with relative success, this should be evaluated by statistical analysis in preparation for potential further waves. Artificial neural networks and logistic regression models were used in this study, and some statistical indicators were extracted to shed light on this pandemic. WHO website data for 32 European countries from 11th of January 2020 to 29th of May 2020 was utilized. The rationale for choosing the stated methodological tools is that the classification accuracy rate of artificial neural networks is 85.6% while the classification accuracy rate of logistic regression models 80.8%. Twit Text FOAVip Artificial neural networks and statistical models for optimization studying COVID-19 ????Results Phys http://www.kidney.de/pget.php?&tw=1&pmid=33996399 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33996399 #FOAvip English Wikipedia <ref>{{Cite pmid|33996399}}</ref> Artificial neural networks and statistical models for optimization studying COVID-19 #MMPMID33996399 Elhag AA; Aloafi TA; Jawa TM; Sayed-Ahmed N; Bayones FS; Bouslimi J Results Phys 2021[Jun]; 25 (ä): 104274 PMID33996399show ga The biggest challenge facing the world in 2020 was the pandemic of the coronavirus disease (COVID-19). Since the start of 2020, COVID-19 has invaded the world, causing death to people and economic damage, which is cause for sadness and anxiety. Since the world has passed from the first peak with relative success, this should be evaluated by statistical analysis in preparation for potential further waves. Artificial neural networks and logistic regression models were used in this study, and some statistical indicators were extracted to shed light on this pandemic. WHO website data for 32 European countries from 11th of January 2020 to 29th of May 2020 was utilized. The rationale for choosing the stated methodological tools is that the classification accuracy rate of artificial neural networks is 85.6% while the classification accuracy rate of logistic regression models 80.8%. äArtificial neural networks and statistical models for optimization stu(epmc).pdf DeepDyve Pubget Overpricing