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10.7150/ijbs.58855 http://scihub22266oqcxt.onion/10.7150/ijbs.58855 33907522!8071762!33907522     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       Int+J+Biol+Sci 2021 ; 17 (6): 1581-1587 Nephropedia Template TP {{tp|p=33907522|t=2021. Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives |pdf=|usr=}}{{33907522}} gab.com Text Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives JO: Int J Biol Sci http://www.kidney.de/pget.php?&tw=1&pmid=33907522 #FOAvip Artificial intelligence (AI) is being used to aid in various aspects of the COVID-19 crisis, including epidemiology, molecular research and drug development, medical diagnosis and treatment, and socioeconomics. The association of AI and COVID-19 can accelerate to rapidly diagnose positive patients. To learn the dynamics of a pandemic with relevance to AI, we search the literature using the different academic databases (PubMed, PubMed Central, Scopus, Google Scholar) and preprint servers (bioRxiv, medRxiv, arXiv). In the present review, we address the clinical applications of machine learning and deep learning, including clinical characteristics, electronic medical records, medical images (CT, X-ray, ultrasound images, etc.) in the COVID-19 diagnosis. The current challenges and future perspectives provided in this review can be used to direct an ideal deployment of AI technology in a pandemic. Twit Text FOAVip Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives ????Int J Biol Sci http://www.kidney.de/pget.php?&tw=1&pmid=33907522 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33907522 #FOAvip English Wikipedia <ref>{{Cite pmid|33907522}}</ref> Artificial intelligence in the diagnosis of COVID-19: challenges and perspectives #MMPMID33907522 Huang S; Yang J; Fong S; Zhao Q Int J Biol Sci 2021[]; 17 (6): 1581-1587 PMID33907522show ga Artificial intelligence (AI) is being used to aid in various aspects of the COVID-19 crisis, including epidemiology, molecular research and drug development, medical diagnosis and treatment, and socioeconomics. The association of AI and COVID-19 can accelerate to rapidly diagnose positive patients. To learn the dynamics of a pandemic with relevance to AI, we search the literature using the different academic databases (PubMed, PubMed Central, Scopus, Google Scholar) and preprint servers (bioRxiv, medRxiv, arXiv). In the present review, we address the clinical applications of machine learning and deep learning, including clinical characteristics, electronic medical records, medical images (CT, X-ray, ultrasound images, etc.) in the COVID-19 diagnosis. The current challenges and future perspectives provided in this review can be used to direct an ideal deployment of AI technology in a pandemic. |*Artificial Intelligence[MESH] |COVID-19 Testing/methods[MESH] |COVID-19/*diagnosis/virology[MESH] |Humans[MESH] |Machine Learning[MESH]Artificial intelligence in the diagnosis of COVID-19: challenges and (epmc).pdf DeepDyve Pubget Overpricing