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10.7717/peerj-cs.564 http://scihub22266oqcxt.onion/10.7717/peerj-cs.564 34141890!8176528!34141890     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 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 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PeerJ+Comput+Sci 2021 ; 7 (ä): e564 Nephropedia Template TP {{tp|p=34141890|t=2021. Overview of current state of research on the application of artificial intelligence techniques for COVID-19 |pdf=|usr=}}{{34141890}} gab.com Text Overview of current state of research on the application of artificial intelligence techniques for COVID-19 JO: PeerJ Comput Sci http://www.kidney.de/pget.php?&tw=1&pmid=34141890 #FOAvip BACKGROUND: Until now, there are still a limited number of resources available to predict and diagnose COVID-19 disease. The design of novel drug-drug interaction for COVID-19 patients is an open area of research. Also, the development of the COVID-19 rapid testing kits is still a challenging task. METHODOLOGY: This review focuses on two prime challenges caused by urgent needs to effectively address the challenges of the COVID-19 pandemic, i.e., the development of COVID-19 classification tools and drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models. RESULTS: In this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease. This study provides recommendations for future research and facilitates knowledge collection and formation on the application of the AI techniques for dealing with the COVID-19 epidemic and its consequences. CONCLUSIONS: The AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients. Twit Text FOAVip Overview of current state of research on the application of artificial intelligence techniques for COVID-19 ????PeerJ Comput Sci http://www.kidney.de/pget.php?&tw=1&pmid=34141890 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34141890 #FOAvip English Wikipedia <ref>{{Cite pmid|34141890}}</ref> Overview of current state of research on the application of artificial intelligence techniques for COVID-19 #MMPMID34141890 Kumar V; Singh D; Kaur M; Damasevicius R PeerJ Comput Sci 2021[]; 7 (ä): e564 PMID34141890show ga BACKGROUND: Until now, there are still a limited number of resources available to predict and diagnose COVID-19 disease. The design of novel drug-drug interaction for COVID-19 patients is an open area of research. Also, the development of the COVID-19 rapid testing kits is still a challenging task. METHODOLOGY: This review focuses on two prime challenges caused by urgent needs to effectively address the challenges of the COVID-19 pandemic, i.e., the development of COVID-19 classification tools and drug discovery models for COVID-19 infected patients with the help of artificial intelligence (AI) based techniques such as machine learning and deep learning models. RESULTS: In this paper, various AI-based techniques are studied and evaluated by the means of applying these techniques for the prediction and diagnosis of COVID-19 disease. This study provides recommendations for future research and facilitates knowledge collection and formation on the application of the AI techniques for dealing with the COVID-19 epidemic and its consequences. CONCLUSIONS: The AI techniques can be an effective tool to tackle the epidemic caused by COVID-19. These may be utilized in four main fields such as prediction, diagnosis, drug design, and analyzing social implications for COVID-19 infected patients. äOverview of current state of research on the application of artificial(epmc).pdf DeepDyve Pubget Overpricing