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10.3201/eid2611.200706 http://scihub22266oqcxt.onion/10.3201/eid2611.200706 33079038!7588519!33079038     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33079038&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 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Emerg+Infect+Dis 2020 ; 26 (11): 2733-2735 Nephropedia Template TP {{tp|p=33079038|t=2020. Thresholds versus Anomaly Detection for Surveillance of Pneumonia and Influenza Mortality |pdf=|usr=}}{{33079038}} gab.com Text Thresholds versus Anomaly Detection for Surveillance of Pneumonia and Influenza Mortality JO: Emerg Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=33079038 #FOAvip Computational surveillance of pneumonia and influenza mortality in the United States using FluView uses epidemic thresholds to identify high mortality rates but is limited by statistical issues such as seasonality and autocorrelation. We used time series anomaly detection to improve recognition of high mortality rates. Results suggest that anomaly detection can complement mortality reporting. Twit Text FOAVip Thresholds versus Anomaly Detection for Surveillance of Pneumonia and Influenza Mortality ????Emerg Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=33079038 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33079038 #FOAvip English Wikipedia <ref>{{Cite pmid|33079038}}</ref> Thresholds versus Anomaly Detection for Surveillance of Pneumonia and Influenza Mortality #MMPMID33079038 Wiemken TL; Rutschman AS; Niemotka SL; Hoft D Emerg Infect Dis 2020[]; 26 (11): 2733-2735 PMID33079038show ga Computational surveillance of pneumonia and influenza mortality in the United States using FluView uses epidemic thresholds to identify high mortality rates but is limited by statistical issues such as seasonality and autocorrelation. We used time series anomaly detection to improve recognition of high mortality rates. Results suggest that anomaly detection can complement mortality reporting. |*Epidemics[MESH] |Data Science[MESH] |Humans[MESH] |Influenza, Human/diagnosis/epidemiology/*mortality[MESH] |Machine Learning[MESH] |Pneumonia/*diagnosis/epidemiology[MESH] |Population Surveillance/*methods[MESH]Thresholds versus Anomaly Detection for Surveillance of Pneumonia and (epmc).pdf DeepDyve Pubget Overpricing