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10.1002/rmv.2205 http://scihub22266oqcxt.onion/10.1002/rmv.2205 33476063!7883226!33476063     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Rev+Med+Virol 2021 ; 31 (5): 1-11 Nephropedia Template TP {{tp|p=33476063|t=2021. How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future |pdf=|usr=}}{{33476063}} gab.com Text How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future JO: Rev Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=33476063 #FOAvip The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI-based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid-19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI-based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better response and preparedness measures against Covid-19 cases. AI-based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid-19 pandemic. Twit Text FOAVip How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future ????Rev Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=33476063 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33476063 #FOAvip English Wikipedia <ref>{{Cite pmid|33476063}}</ref> How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future #MMPMID33476063 Malik YS; Sircar S; Bhat S; Ansari MI; Pande T; Kumar P; Mathapati B; Balasubramanian G; Kaushik R; Natesan S; Ezzikouri S; El Zowalaty ME; Dhama K Rev Med Virol 2021[Sep]; 31 (5): 1-11 PMID33476063show ga The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declare it a pandemic. Traditional epidemiological tools are being significantly complemented by recent innovations especially using artificial intelligence (AI) and machine learning. AI-based model systems could improve pattern recognition of disease spread in populations and predictions of outbreaks in different geographical locations. A variable and a minimal amount of data are available for the signs and symptoms of Covid-19, allowing a composite of maximum likelihood algorithms to be employed to enhance the accuracy of disease diagnosis and to identify potential drugs. AI-based forecasting and predictions are expected to complement traditional approaches by helping public health officials to select better response and preparedness measures against Covid-19 cases. AI-based approaches have helped address the key issues but a significant impact on the global healthcare industry is yet to be achieved. The capability of AI to address the challenges may make it a key player in the operation of healthcare systems in future. Here, we present an overview of the prospective applications of the AI model systems in healthcare settings during the ongoing Covid-19 pandemic. |*Artificial Intelligence[MESH] |*Delivery of Health Care[MESH] |COVID-19/*epidemiology[MESH] |Humans[MESH]How artificial intelligence may help the Covid-19 pandemic: Pitfalls a(epmc).pdf DeepDyve Pubget Overpricing