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10.1186/s12911-020-01321-9 http://scihub22266oqcxt.onion/10.1186/s12911-020-01321-9 33256719!7702206!33256719     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       BMC+Med+Inform+Decis+Mak 2020 ; 20 (1): 309 Nephropedia Template TP {{tp|p=33256719|t=2020. The emerging COVID-19 research: dynamic and regularly updated science maps and analyses |pdf=|usr=}}{{33256719}} gab.com Text The emerging COVID-19 research: dynamic and regularly updated science maps and analyses JO: BMC Med Inform Decis Mak http://www.kidney.de/pget.php?&tw=1&pmid=33256719 #FOAvip BACKGROUND: The COVID-19 pandemic is a global public health emergency and experts emphasize the need for rapid and a high degree of communication and interaction between all parties, in order for critical research to be implemented. We introduce a resource (website) that provides bibliometric analysis showing the current content and structure of the published literature. As new research is published daily, the analysis is regularly updated to show the status as the research field develops and matures. METHODS: Two bibliometric methods were employed, the first is a keyword co-occurrence analysis, based on published work available from PubMed. The second is a bibliometric coupling analysis, based on articles available through Scopus. The results are presented as clustered network graphs; available as interactive network graphs through the webpage. RESULTS: For research as of March 23rd, keyword co-occurrence analysis showed that research was organized in 4 topic clusters: "Health and pandemic management", "The disease and its pathophysiology", "Clinical epidemiology of the disease" and "Treatment of the disease". Coupling analyses resulted in 4 clusters on literature that relates to "Overview of the new virus", "Clinical medicine", "On the virus" and "Reproduction rate and spread". CONCLUSION: We introduced a dynamic resource that will give a wide readership an overview of how the structure of the COVID-19 literature is developing. To illustrate what this can look like, we showed the structure as it stands three months after the virus was identified; the structure is likely to change as we progress to later stages of this pandemic. Twit Text FOAVip The emerging COVID-19 research: dynamic and regularly updated science maps and analyses ????BMC Med Inform Decis Mak http://www.kidney.de/pget.php?&tw=1&pmid=33256719 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33256719 #FOAvip English Wikipedia <ref>{{Cite pmid|33256719}}</ref> The emerging COVID-19 research: dynamic and regularly updated science maps and analyses #MMPMID33256719 Andersen N; Bramness JG; Lund IO BMC Med Inform Decis Mak 2020[Nov]; 20 (1): 309 PMID33256719show ga BACKGROUND: The COVID-19 pandemic is a global public health emergency and experts emphasize the need for rapid and a high degree of communication and interaction between all parties, in order for critical research to be implemented. We introduce a resource (website) that provides bibliometric analysis showing the current content and structure of the published literature. As new research is published daily, the analysis is regularly updated to show the status as the research field develops and matures. METHODS: Two bibliometric methods were employed, the first is a keyword co-occurrence analysis, based on published work available from PubMed. The second is a bibliometric coupling analysis, based on articles available through Scopus. The results are presented as clustered network graphs; available as interactive network graphs through the webpage. RESULTS: For research as of March 23rd, keyword co-occurrence analysis showed that research was organized in 4 topic clusters: "Health and pandemic management", "The disease and its pathophysiology", "Clinical epidemiology of the disease" and "Treatment of the disease". Coupling analyses resulted in 4 clusters on literature that relates to "Overview of the new virus", "Clinical medicine", "On the virus" and "Reproduction rate and spread". CONCLUSION: We introduced a dynamic resource that will give a wide readership an overview of how the structure of the COVID-19 literature is developing. To illustrate what this can look like, we showed the structure as it stands three months after the virus was identified; the structure is likely to change as we progress to later stages of this pandemic. |*Bibliometrics[MESH] |*COVID-19[MESH] |Biomedical Research/*trends[MESH] |Humans[MESH] |Pandemics[MESH]The emerging COVID-19 research: dynamic and regularly updated science (epmc).pdf DeepDyve Pubget Overpricing