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10.1016/j.scitotenv.2020.142810 http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2020.142810 33097268!7550892!33097268     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Total+Environ 2021 ; 764 (ä): 142810 Nephropedia Template TP {{tp|p=33097268|t=2021. Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach |pdf=|usr=}}{{33097268}} gab.com Text Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach JO: Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=33097268 #FOAvip The COVID-19 virus has infected more than 38 million people and resulted in more than one million deaths worldwide as of October 14, 2020. By using the logistic regression model, we identified novel critical factors associated with COVID19 cases, death, and case fatality rates in 154 countries and in the 50 U.S. states. Among numerous factors associated with COVID-19 risk, economic inequality enhanced the risk of COVID-19 transmission. The per capita hospital beds correlated negatively with COVID-19 deaths. Blood types B and AB were protective factors for COVID-19 risk, while blood type A was a risk factor. The prevalence of HIV and influenza and pneumonia was associated with reduced COVID-19 risk. Increased intake of vegetables, edible oil, protein, vitamin D, and vitamin K was associated with reduced COVID-19 risk, while increased intake of alcohol was associated with increased COVID-19 risk. Other factors included age, sex, temperature, humidity, social distancing, smoking, health investment, urbanization level, and race. High temperature is a more compelling factor mitigating COVID-19 transmission than low temperature. Our comprehensive identification of the factors affecting COVID-19 transmission and fatality may provide new insights into the COVID-19 pandemic and advise effective strategies for preventing and migrating COVID-19 spread. Twit Text FOAVip Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach ????Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=33097268 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33097268 #FOAvip English Wikipedia <ref>{{Cite pmid|33097268}}</ref> Identifying novel factors associated with COVID-19 transmission and fatality using the machine learning approach #MMPMID33097268 Li M; Zhang Z; Cao W; Liu Y; Du B; Chen C; Liu Q; Uddin MN; Jiang S; Chen C; Zhang Y; Wang X Sci Total Environ 2021[Apr]; 764 (ä): 142810 PMID33097268show ga The COVID-19 virus has infected more than 38 million people and resulted in more than one million deaths worldwide as of October 14, 2020. By using the logistic regression model, we identified novel critical factors associated with COVID19 cases, death, and case fatality rates in 154 countries and in the 50 U.S. states. Among numerous factors associated with COVID-19 risk, economic inequality enhanced the risk of COVID-19 transmission. The per capita hospital beds correlated negatively with COVID-19 deaths. Blood types B and AB were protective factors for COVID-19 risk, while blood type A was a risk factor. The prevalence of HIV and influenza and pneumonia was associated with reduced COVID-19 risk. Increased intake of vegetables, edible oil, protein, vitamin D, and vitamin K was associated with reduced COVID-19 risk, while increased intake of alcohol was associated with increased COVID-19 risk. Other factors included age, sex, temperature, humidity, social distancing, smoking, health investment, urbanization level, and race. High temperature is a more compelling factor mitigating COVID-19 transmission than low temperature. Our comprehensive identification of the factors affecting COVID-19 transmission and fatality may provide new insights into the COVID-19 pandemic and advise effective strategies for preventing and migrating COVID-19 spread. |*COVID-19[MESH] |*Coronavirus Infections/epidemiology[MESH] |Adolescent[MESH] |Aged[MESH] |Child[MESH] |Child, Preschool[MESH] |Female[MESH] |Humans[MESH] |Infant[MESH] |Machine Learning[MESH] |Male[MESH] |Pandemics[MESH] |SARS-CoV-2[MESH]Identifying novel factors associated with COVID-19 transmission and fa(epmc).pdf DeepDyve Pubget Overpricing