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10.1371/journal.pone.0239694 http://scihub22266oqcxt.onion/10.1371/journal.pone.0239694 32997699!7526926!32997699     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       PLoS+One 2020 ; 15 (9): e0239694 Nephropedia Template TP {{tp|p=32997699|t=2020. Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach |pdf=|usr=}}{{32997699}} gab.com Text Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach JO: PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=32997699 #FOAvip With the novel COVID-19 pandemic disrupting and threatening the lives of millions, researchers and clinicians have been recently conducting clinical trials at an unprecedented rate to learn more about the virus and potential drugs/treatments/vaccines to treat its infection. As a result of the influx of clinical trials, researchers, clinicians, and the lay public, now more than ever, face a significant challenge in keeping up-to-date with the rapid rate of discoveries and advances. To remedy this problem, this research mined the ClinicalTrials.gov corpus to extract COVID-19 related clinical trials, produce unique reports to summarize findings and make the meta-data available via Application Programming Interfaces (APIs). Unique reports were created for each drug/intervention, Medical Subject Heading (MeSH) term, and Human Phenotype Ontology (HPO) term. These reports, which have been run over multiple time points, along with APIs to access meta-data, are freely available at http://covidresearchtrials.com. The pipeline, reports, association of COVID-19 clinical trials with MeSH and HPO terms, insights, public repository, APIs, and correlations produced are all novel in this work. The freely available, novel resources present up-to-date relevant biological information and insights in a robust, accessible manner, illustrating their invaluable potential to aid researchers overcome COVID-19 and save hundreds of thousands of lives. Twit Text FOAVip Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach ????PLoS One http://www.kidney.de/pget.php?&tw=1&pmid=32997699 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32997699 #FOAvip English Wikipedia <ref>{{Cite pmid|32997699}}</ref> Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach #MMPMID32997699 Alag S PLoS One 2020[]; 15 (9): e0239694 PMID32997699show ga With the novel COVID-19 pandemic disrupting and threatening the lives of millions, researchers and clinicians have been recently conducting clinical trials at an unprecedented rate to learn more about the virus and potential drugs/treatments/vaccines to treat its infection. As a result of the influx of clinical trials, researchers, clinicians, and the lay public, now more than ever, face a significant challenge in keeping up-to-date with the rapid rate of discoveries and advances. To remedy this problem, this research mined the ClinicalTrials.gov corpus to extract COVID-19 related clinical trials, produce unique reports to summarize findings and make the meta-data available via Application Programming Interfaces (APIs). Unique reports were created for each drug/intervention, Medical Subject Heading (MeSH) term, and Human Phenotype Ontology (HPO) term. These reports, which have been run over multiple time points, along with APIs to access meta-data, are freely available at http://covidresearchtrials.com. The pipeline, reports, association of COVID-19 clinical trials with MeSH and HPO terms, insights, public repository, APIs, and correlations produced are all novel in this work. The freely available, novel resources present up-to-date relevant biological information and insights in a robust, accessible manner, illustrating their invaluable potential to aid researchers overcome COVID-19 and save hundreds of thousands of lives. |*Biological Ontologies[MESH] |*Clinical Trials as Topic[MESH] |*Natural Language Processing[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Computational Biology[MESH] |Coronavirus Infections/*therapy[MESH] |Humans[MESH] |Internet[MESH] |Medical Subject Headings[MESH] |Pandemics[MESH] |Phenotype[MESH] |Pneumonia, Viral/*therapy[MESH] |SARS-CoV-2[MESH]Analysis of COVID-19 clinical trials: A data-driven, ontology-based, a(epmc).pdf DeepDyve Pubget Overpricing