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10.1080/19466315.2020.1797867 http://scihub22266oqcxt.onion/10.1080/19466315.2020.1797867 34191983!8011491!34191983     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=34191983&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\34191983.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Stat+Biopharm+Res 2020 ; 12 (4): 506-517 Nephropedia Template TP {{tp|p=34191983|t=2020. Machine learning for clinical trials in the era of COVID-19 |pdf=|usr=}}{{34191983}} gab.com Text Machine learning for clinical trials in the era of COVID-19 JO: Stat Biopharm Res http://www.kidney.de/pget.php?&tw=1&pmid=34191983 #FOAvip The world is in the midst of a pandemic. We still know little about the disease COVID-19 or about the virus (SARS-CoV-2) that causes it. We do not have a vaccine or a treatment (aside from managing symptoms). We do not know if recovery from COVID-19 produces immunity, and if so for how long, hence we do not know if "herd immunity" will eventually reduce the risk or if a successful vaccine can be developed - and this knowledge may be a long time coming. In the meantime, the COVID-19 pandemic is presenting enormous challenges to medical research, and to clinical trials in particular. This paper identifies some of those challenges and suggests ways in which machine learning can help in response to those challenges. We identify three areas of challenge: ongoing clinical trials for non-COVID-19 drugs; clinical trials for repurposing drugs to treat COVID-19, and clinical trials for new drugs to treat COVID-19. Within each of these areas, we identify aspects for which we believe machine learning can provide invaluable assistance. Twit Text FOAVip Machine learning for clinical trials in the era of COVID-19 ????Stat Biopharm Res http://www.kidney.de/pget.php?&tw=1&pmid=34191983 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34191983 #FOAvip English Wikipedia <ref>{{Cite pmid|34191983}}</ref> Machine learning for clinical trials in the era of COVID-19 #MMPMID34191983 Zame WR; Bica I; Shen C; Curth A; Lee HS; Bailey S; Weatherall J; Wright D; Bretz F; van der Schaar M Stat Biopharm Res 2020[Aug]; 12 (4): 506-517 PMID34191983show ga The world is in the midst of a pandemic. We still know little about the disease COVID-19 or about the virus (SARS-CoV-2) that causes it. We do not have a vaccine or a treatment (aside from managing symptoms). We do not know if recovery from COVID-19 produces immunity, and if so for how long, hence we do not know if "herd immunity" will eventually reduce the risk or if a successful vaccine can be developed - and this knowledge may be a long time coming. In the meantime, the COVID-19 pandemic is presenting enormous challenges to medical research, and to clinical trials in particular. This paper identifies some of those challenges and suggests ways in which machine learning can help in response to those challenges. We identify three areas of challenge: ongoing clinical trials for non-COVID-19 drugs; clinical trials for repurposing drugs to treat COVID-19, and clinical trials for new drugs to treat COVID-19. Within each of these areas, we identify aspects for which we believe machine learning can provide invaluable assistance. äMachine learning for clinical trials in the era of COVID-19 (epmc).pdf DeepDyve Pubget Overpricing