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10.1016/j.cell.2020.04.045 http://scihub22266oqcxt.onion/10.1016/j.cell.2020.04.045 32416069!7196900!32416069     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Cell 2020 ; 181 (6): 1423-1433.e11 Nephropedia Template TP {{tp|p=32416069|t=2020. Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography |pdf=|usr=}}{{32416069}} gab.com Text Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography JO: Cell http://www.kidney.de/pget.php?&tw=1&pmid=32416069 #FOAvip Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19. Twit Text FOAVip Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography ????Cell http://www.kidney.de/pget.php?&tw=1&pmid=32416069 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32416069 #FOAvip English Wikipedia <ref>{{Cite pmid|32416069}}</ref> Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography #MMPMID32416069 Zhang K; Liu X; Shen J; Li Z; Sang Y; Wu X; Zha Y; Liang W; Wang C; Wang K; Ye L; Gao M; Zhou Z; Li L; Wang J; Yang Z; Cai H; Xu J; Yang L; Cai W; Xu W; Wu S; Zhang W; Jiang S; Zheng L; Zhang X; Wang L; Lu L; Li J; Yin H; Wang W; Li O; Zhang C; Liang L; Wu T; Deng R; Wei K; Zhou Y; Chen T; Lau JY; Fok M; He J; Lin T; Li W; Wang G Cell 2020[Jun]; 181 (6): 1423-1433.e11 PMID32416069show ga Many COVID-19 patients infected by SARS-CoV-2 virus develop pneumonia (called novel coronavirus pneumonia, NCP) and rapidly progress to respiratory failure. However, rapid diagnosis and identification of high-risk patients for early intervention are challenging. Using a large computed tomography (CT) database from 3,777 patients, we developed an AI system that can diagnose NCP and differentiate it from other common pneumonia and normal controls. The AI system can assist radiologists and physicians in performing a quick diagnosis especially when the health system is overloaded. Significantly, our AI system identified important clinical markers that correlated with the NCP lesion properties. Together with the clinical data, our AI system was able to provide accurate clinical prognosis that can aid clinicians to consider appropriate early clinical management and allocate resources appropriately. We have made this AI system available globally to assist the clinicians to combat COVID-19. |*Artificial Intelligence[MESH] |*Tomography, X-Ray Computed[MESH] |COVID-19[MESH] |China[MESH] |Cohort Studies[MESH] |Coronavirus Infections/*diagnosis/pathology/therapy[MESH] |Datasets as Topic[MESH] |Humans[MESH] |Lung/pathology[MESH] |Models, Biological[MESH] |Pandemics[MESH] |Pilot Projects[MESH] |Pneumonia, Viral/*diagnosis/pathology/therapy[MESH] |Prognosis[MESH] |Radiologists[MESH]Clinically Applicable AI System for Accurate Diagnosis, Quantitative (epmc).pdf DeepDyve Pubget Overpricing