id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-273035-sewfb3q8	Kang, Xixiong	Proteomic Fingerprints for Potential Application to Early Diagnosis of Severe Acute Respiratory Syndrome	2005-01-01		.txt	text/plain	4128	177	50	Background: Definitive early-stage diagnosis of severe acute respiratory syndrome (SARS) is important despite the number of laboratory tests that have been developed to complement clinical features and epidemiologic data in case definition. Results: The discriminatory classifier with a panel of four biomarkers determined in the training set could precisely detect 36 of 37 (sensitivity, 97.3%) acute SARS and 987 of 993 (specificity, 99.4%) non-SARS samples. We established a decision tree algorithm consisting of four unique biomarkers for acute SARS in the training set and subsequently validated the accuracy of this classifier by use of a completely blinded test set. To identify the serum biomarkers that could distinguish SARS from non-SARS samples, we used a training set of specimens (37 SARS acute and 74 controls; Tables 1 and 2) and constructed the decision tree classification algorithm using 10 989 peaks [99 peaks ϫ (37 ϩ 74) spectra] of statistical significance identified in the low energy readings (see Materials and Methods).	./cache/cord-273035-sewfb3q8.txt	./txt/cord-273035-sewfb3q8.txt