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10.1038/s41598-020-71114-7 http://scihub22266oqcxt.onion/10.1038/s41598-020-71114-7 32820210!7441177!32820210     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2020 ; 10 (1): 14042 Nephropedia Template TP {{tp|p=32820210|t=2020. A prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings |pdf=|usr=}}{{32820210}} gab.com Text A prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=32820210 #FOAvip The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in thousands of deaths in the world. Information about prediction model of prognosis of SARS-CoV-2 infection is scarce. We used machine learning for processing laboratory findings of 110 patients with SARS-CoV-2 pneumonia (including 51 non-survivors and 59 discharged patients). The maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator logistic regression model were used for selection of laboratory features. Seven laboratory features selected in the model were: prothrombin activity, urea, white blood cell, interleukin-2 receptor, indirect bilirubin, myoglobin, and fibrinogen degradation products. The signature constructed using the seven features had 98% [93%, 100%] sensitivity and 91% [84%, 99%] specificity in predicting outcome of SARS-CoV-2 pneumonia. Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings. Twit Text FOAVip A prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=32820210 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32820210 #FOAvip English Wikipedia <ref>{{Cite pmid|32820210}}</ref> A prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings #MMPMID32820210 Wu G; Zhou S; Wang Y; Lv W; Wang S; Wang T; Li X Sci Rep 2020[Aug]; 10 (1): 14042 PMID32820210show ga The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in thousands of deaths in the world. Information about prediction model of prognosis of SARS-CoV-2 infection is scarce. We used machine learning for processing laboratory findings of 110 patients with SARS-CoV-2 pneumonia (including 51 non-survivors and 59 discharged patients). The maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator logistic regression model were used for selection of laboratory features. Seven laboratory features selected in the model were: prothrombin activity, urea, white blood cell, interleukin-2 receptor, indirect bilirubin, myoglobin, and fibrinogen degradation products. The signature constructed using the seven features had 98% [93%, 100%] sensitivity and 91% [84%, 99%] specificity in predicting outcome of SARS-CoV-2 pneumonia. Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia based on laboratory findings. |*Models, Statistical[MESH] |Aged[MESH] |Betacoronavirus/*genetics[MESH] |Bilirubin/blood[MESH] |COVID-19[MESH] |Coronavirus Infections/*blood/therapy/virology[MESH] |Data Accuracy[MESH] |Feasibility Studies[MESH] |Female[MESH] |Fibrin Fibrinogen Degradation Products/analysis[MESH] |Forecasting/methods[MESH] |Humans[MESH] |Leukocytes[MESH] |Machine Learning[MESH] |Male[MESH] |Myoglobin/blood[MESH] |Pandemics[MESH] |Pneumonia, Viral/*blood/therapy/virology[MESH] |Prognosis[MESH] |Prothrombin/analysis[MESH] |Receptors, Interleukin-2/blood[MESH] |Retrospective Studies[MESH] |SARS-CoV-2[MESH] |Sensitivity and Specificity[MESH] |Treatment Outcome[MESH]A prediction model of outcome of SARS-CoV-2 pneumonia based on laborat(epmc).pdf DeepDyve Pubget Overpricing