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The capacity of regional cortical average thickness to discriminate between the CN− and CN+ groups was assessed by logistic regression followed by receiving operating characteristic (ROC) curve analysis.
The diagnostic performance of the anti-MCV was comparable with the anti-CCP2 assay for the diagnosis of RA according to the calculated area under the curve (0.824; 95% confidence interval (CI) 0.778 0.870 versus 0.818; 95% CI 0.767 0.869) as analysed by receiving operating characteristic curve.
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An alternative measure of the degree of correspondence between the intra-burst spike count and input phases is given by receiving operating characteristics (ROC) curves (see supporting Text S4).
The performance of these different methods was assessed by a receiving operating characteristic (ROC) method.
The cut-off point for each of the biomarkers was determined by means of a receiving operating characteristic (ROC) curve.
Continuous variables including monthly income, body weight, height, leisure-time physical activity, MMSE score, peak expiratory flow rate, average hand grip strength, and total BMD value were all categorized into two groups according to the cut-off point selected by the Youden index in the receiving operating characteristic (ROC) curves.
The ability of the score to predict the outcome glycemia ≥ 140 mg/dl control at discharge and the best cut off value of the score were assessed by measuring the area under the receiving operating characteristic (ROC) curve in the testing population [ 30].
To assess the fraction of incorrect classifications produced by different thresholds, we plotted the ROC (Receiving Operating Characteristic) curve for this AIs-Deletions matrix (Figure 6B).
For anti-CCP2 and anti-MCV, the receiving operating characteristic (ROC) curve was constructed by plotting sensitivity against one minus specificity (1 – specificity), varying the cutoffs [ 9, 26].
The sensitivity and specificity of variables retained by a multivariable analysis as being associated with neurological outcome was evaluated using receiving operating characteristic (ROC) curves with the corresponding area under the curve (AUC).
area under the receiving operating characteristic curve.
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