<p>The values indicated are weighted averages for the three classes under consideration; control, MCIna and MCIa. Results are shown for the 7 datasets – 100 voxels, 250 voxels, 500 voxels, 750 voxels, 1000 voxels, 2000 voxels and 3000 voxels. The voxels comprising these reduced datasets were selected by the ReliefF algorithm.</p
Areas under the curve (AUC)-values (95% CI) are 0.7679 (95% CI 0.64768 to 0.88812), 0.8648 (95% CI 0...
The ROC curves in the training (A), internal validation (B) and external validation (C) groups. The ...
a<p>AUC: Area Under the receiver operating characteristic (ROC) Curve.</p>b<p>Sens. and spec. are th...
<p>The values indicated are weighted averages for the two classes under consideration; i.e. control ...
<p>Sensitivity and specificity values were obtained for increasing classification thresholds to prod...
<p>Shown here are the ROC curve Area-Under-Curve (AUC) scores, sensitivities and specificities for t...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
<p>The area under the curve (AUC) is 0.76, suggesting a strong ability to discriminate between true ...
<p>This translated into a sensitivity = 88% and specificity = 72% for discriminating between progres...
<p>The areas under the ROC curves, or AUC are 0.93, 0.96, 0.90, and 0.94 for iMcRNA-PseSSC, iMcRNA-E...
<p>ROC curves and their corresponding area under the curve (AUC) values were calculated for each of ...
<p>ROC curves showing sensitivity and specificity for the combination of HbF, A1M and Hpx (<b>A</b>)...
<p>The ROC curve is plotted with the <i>Sn</i> as the <i>y</i>-axis and 1 − <i>Sp</i> as the <i>x</i...
Areas under the curve (AUC)-values (95% CI) are 0.7679 (95% CI 0.64768 to 0.88812), 0.8648 (95% CI 0...
The ROC curves in the training (A), internal validation (B) and external validation (C) groups. The ...
a<p>AUC: Area Under the receiver operating characteristic (ROC) Curve.</p>b<p>Sens. and spec. are th...
<p>The values indicated are weighted averages for the two classes under consideration; i.e. control ...
<p>Sensitivity and specificity values were obtained for increasing classification thresholds to prod...
<p>Shown here are the ROC curve Area-Under-Curve (AUC) scores, sensitivities and specificities for t...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
In this paper we investigate the use of the area under the receiver operating characteristic (ROC) c...
<p>The area under the curve (AUC) is 0.76, suggesting a strong ability to discriminate between true ...
<p>This translated into a sensitivity = 88% and specificity = 72% for discriminating between progres...
<p>The areas under the ROC curves, or AUC are 0.93, 0.96, 0.90, and 0.94 for iMcRNA-PseSSC, iMcRNA-E...
<p>ROC curves and their corresponding area under the curve (AUC) values were calculated for each of ...
<p>ROC curves showing sensitivity and specificity for the combination of HbF, A1M and Hpx (<b>A</b>)...
<p>The ROC curve is plotted with the <i>Sn</i> as the <i>y</i>-axis and 1 − <i>Sp</i> as the <i>x</i...
Areas under the curve (AUC)-values (95% CI) are 0.7679 (95% CI 0.64768 to 0.88812), 0.8648 (95% CI 0...
The ROC curves in the training (A), internal validation (B) and external validation (C) groups. The ...
a<p>AUC: Area Under the receiver operating characteristic (ROC) Curve.</p>b<p>Sens. and spec. are th...