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10.1088/1757-899X/862/4/042037 http://scihub22266oqcxt.onion/10.1088/1757-899X/862/4/042037 C7350573!7350573!34191947     free     free     free       IOP+Conf+Ser+Mater+Sci+Eng 2020 ; 862 (4): ä Nephropedia Template TP {{tp|p=34191947|t=2020. Clustering of Covid-19 morbidity cases in Germany |pdf=|usr=}}{{34191947}} gab.com Text Clustering of Covid-19 morbidity cases in Germany JO: IOP Conf Ser Mater Sci Eng http://www.kidney.de/pget.php?&tw=1&pmid=34191947 #FOAvip The Covid-19 coronavirus has spread almost all over the world. Though it has been reported recently that the epidemic declines in China, in other countries it still hasn?t achieved peak level. The data analysis methods may help struggling against the disease. The Covid-19 Tracking Germany dataset has been handled in the research. It?s daily refreshed dataset available at the kaggle.com site. It contains information on number of fallen ill people in Germany. The cases are grouped by federal land, city, age diapason and date. The main goal of the research is to underline differences in morbidity registered in different lands of Germany. There have been published new suggestions about connection between coronavirus morbidity and BCG vaccination. This question is also taken into account. Analysis based on the handled dataset is able to make only oblique conclusions because of lack of information. Differences in coronavirus morbidity in various regions and various age groups are highlighted. The regions of Germany are clustered into groups by gravity of recent situation. Twit Text FOAVip Clustering of Covid-19 morbidity cases in Germany ????IOP Conf Ser Mater Sci Eng http://www.kidney.de/pget.php?&tw=1&pmid=34191947 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34191947 #FOAvip English Wikipedia <ref>{{Cite pmid|34191947}}</ref> Clustering of Covid-19 morbidity cases in Germany #MMPMID34191947 Petrusevich DA IOP Conf Ser Mater Sci Eng 2020[May]; 862 (4): ä PMID34191947show ga The Covid-19 coronavirus has spread almost all over the world. Though it has been reported recently that the epidemic declines in China, in other countries it still hasn?t achieved peak level. The data analysis methods may help struggling against the disease. The Covid-19 Tracking Germany dataset has been handled in the research. It?s daily refreshed dataset available at the kaggle.com site. It contains information on number of fallen ill people in Germany. The cases are grouped by federal land, city, age diapason and date. The main goal of the research is to underline differences in morbidity registered in different lands of Germany. There have been published new suggestions about connection between coronavirus morbidity and BCG vaccination. This question is also taken into account. Analysis based on the handled dataset is able to make only oblique conclusions because of lack of information. Differences in coronavirus morbidity in various regions and various age groups are highlighted. The regions of Germany are clustered into groups by gravity of recent situation. äClustering of Covid-19 morbidity cases in Germany (epmc).pdf DeepDyve Pubget Overpricing