id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-347288-ub0l4mov	Yin, Xi	Assessment of the Severity of Coronavirus Disease: Quantitative Computed Tomography Parameters versus Semiquantitative Visual Score	2020-06-11		.txt	text/plain	2863	164	47	OBJECTIVE: To compare the accuracies of quantitative computed tomography (CT) parameters and semiquantitative visual score in evaluating clinical classification of severity of coronavirus disease (COVID-19). To classify the severity of COVID-19, area under the curve of the percentage of lesions was the highest (0.807; 95% confidence interval, 0.744–0.861: p < 0.001) and that of the quantitative CT parameters was significantly higher than that of the semiquantitative visual score (p = 0.001). The aim of this study was to use an open-source software platform to compare the accuracy of the clinical classification of the severity of COVID-19 based on quantitative CT parameters and the semiquantitative visual score. Table 5 shows the cutoff values, sensitivity, specificity, area under the curve (AUC) and 95% confidence interval when the chest CT images of all subjects were assessed with the two different systems: the quantitative CT parameters were more accurate than the semiquantitative visual score for determination of the severity of COVID-19.	./cache/cord-347288-ub0l4mov.txt	./txt/cord-347288-ub0l4mov.txt