<p>ROC curve and prediction parameters for optimal thresholds in all tested methods.</p
<p>The ROC curves for evaluating the quality of the algorithms over the entire test datasets.</p
<p>Receiver operating characteristic curves (ROC) determining potential for PT prediction using four...
<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM p...
<p>ROC Curve of the linear regression equation proposed as a prediction model for AHI.</p
<p>ROC curve for logistic regression, the best model found on the reduced feature set (discovery).</...
<p>ROC curve for the best model found on the reduced feature set (replication).</p
<p>ROC curve for the combined parameter TBR10 + TBR difference; Threshold = 1.602.</p
<p>ROC curves for the determination of the overall performance of the assay and the optimal cut-off ...
<p>ROC curve to identify optimal criterion for variables at baseline, using characteristics of the p...
A two-parameter exponential equation for modeling a receiver operating characteristic (ROC) curve is...
<p>ROC curve for the best model found on the reduced feature set (discovery).</p
<p>The curve presents the true positive rate (or sensitivity) in function of false positive rate for...
<p>ROC curve analysis of each baseline parameter and prediction of hyperbilirubinemia.</p
<p>Sensitivity and specificity was maximized at a sensitivity of 0.858 and specificity of 0.623.</p
(A) Performance of the model in the training set, which showed an AUC value of 0.768, an optimal cut...
<p>The ROC curves for evaluating the quality of the algorithms over the entire test datasets.</p
<p>Receiver operating characteristic curves (ROC) determining potential for PT prediction using four...
<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM p...
<p>ROC Curve of the linear regression equation proposed as a prediction model for AHI.</p
<p>ROC curve for logistic regression, the best model found on the reduced feature set (discovery).</...
<p>ROC curve for the best model found on the reduced feature set (replication).</p
<p>ROC curve for the combined parameter TBR10 + TBR difference; Threshold = 1.602.</p
<p>ROC curves for the determination of the overall performance of the assay and the optimal cut-off ...
<p>ROC curve to identify optimal criterion for variables at baseline, using characteristics of the p...
A two-parameter exponential equation for modeling a receiver operating characteristic (ROC) curve is...
<p>ROC curve for the best model found on the reduced feature set (discovery).</p
<p>The curve presents the true positive rate (or sensitivity) in function of false positive rate for...
<p>ROC curve analysis of each baseline parameter and prediction of hyperbilirubinemia.</p
<p>Sensitivity and specificity was maximized at a sensitivity of 0.858 and specificity of 0.623.</p
(A) Performance of the model in the training set, which showed an AUC value of 0.768, an optimal cut...
<p>The ROC curves for evaluating the quality of the algorithms over the entire test datasets.</p
<p>Receiver operating characteristic curves (ROC) determining potential for PT prediction using four...
<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM p...
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