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10.3390/diagnostics11081309 http://scihub22266oqcxt.onion/10.3390/diagnostics11081309 34441244!8392709!34441244     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       Diagnostics+(Basel) 2021 ; 11 (8): ä Nephropedia Template TP {{tp|p=34441244|t=2021. Forecasting COVID-19 Severity by Intelligent Optical Fingerprinting of Blood Samples |pdf=|usr=}}{{34441244}} gab.com Text Forecasting COVID-19 Severity by Intelligent Optical Fingerprinting of Blood Samples JO: Diagnostics (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=34441244 #FOAvip Forecasting COVID-19 disease severity is key to supporting clinical decision making and assisting resource allocation, particularly in intensive care units (ICUs). Here, we investigated the utility of time- and frequency-related features of the backscattered signal of serum patient samples to predict COVID-19 disease severity immediately after diagnosis. ICU admission was the primary outcome used to define disease severity. We developed a stacking ensemble machine learning model including the backscattered signal features (optical fingerprint), patient comorbidities, and age (AUROC = 0.80), which significantly outperformed the predictive value of clinical and laboratory variables available at hospital admission (AUROC = 0.71). The information derived from patient optical fingerprints was not strongly correlated with any clinical/laboratory variable, suggesting that optical fingerprinting brings unique information for COVID-19 severity risk assessment. Optical fingerprinting is a label-free, real-time, and low-cost technology that can be easily integrated as a front-line tool to facilitate the triage and clinical management of COVID-19 patients. Twit Text FOAVip Forecasting COVID-19 Severity by Intelligent Optical Fingerprinting of Blood Samples ????Diagnostics (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=34441244 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34441244 #FOAvip English Wikipedia <ref>{{Cite pmid|34441244}}</ref> Forecasting COVID-19 Severity by Intelligent Optical Fingerprinting of Blood Samples #MMPMID34441244 Faria SP; Carpinteiro C; Pinto V; Rodrigues SM; Alves J; Marques F; Lourenco M; Santos PH; Ramos A; Cardoso MJ; Guimaraes JT; Rocha S; Sampaio P; Clifton DA; Mumtaz M; Paiva JS Diagnostics (Basel) 2021[Jul]; 11 (8): ä PMID34441244show ga Forecasting COVID-19 disease severity is key to supporting clinical decision making and assisting resource allocation, particularly in intensive care units (ICUs). Here, we investigated the utility of time- and frequency-related features of the backscattered signal of serum patient samples to predict COVID-19 disease severity immediately after diagnosis. ICU admission was the primary outcome used to define disease severity. We developed a stacking ensemble machine learning model including the backscattered signal features (optical fingerprint), patient comorbidities, and age (AUROC = 0.80), which significantly outperformed the predictive value of clinical and laboratory variables available at hospital admission (AUROC = 0.71). The information derived from patient optical fingerprints was not strongly correlated with any clinical/laboratory variable, suggesting that optical fingerprinting brings unique information for COVID-19 severity risk assessment. Optical fingerprinting is a label-free, real-time, and low-cost technology that can be easily integrated as a front-line tool to facilitate the triage and clinical management of COVID-19 patients. äForecasting COVID-19 Severity by Intelligent Optical Fingerprinting of(epmc).pdf DeepDyve Pubget Overpricing