ROC curves of the model under non-feature selection, feature selection, and mixed sampling.</p
ROC curves of the PR (a) and CR (b) model for the best and worst training (solid) and the validation...
<p>ROC curves for the two models of the development set using leave-one-out cross-validation (LOOCV)...
ROC curves for the mortality model, using test data (AUC values are indicated on the graph).</p
<p>ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p
ROC curves of the methods with different features for representing images and different classifiers....
<p>ROC curve for the best model found on the reduced feature set (replication).</p
<p>ROC curve for the best model found on the reduced feature set (discovery).</p
ROC curves for the top performing model compared to individual feature predictions.</p
<p>ROC curve for logistic regression, the best model found on the reduced feature set (discovery).</...
<p>ROC Curves with (+) or without (−) boundary detection (BD) and model fitness check (MFC).</p
ROC curves for logistic regression models for each outcome, using penalised regression of full paren...
<p>ROC Curve of different classification methods (SVM only, GA+SVM, GA+SVM+Post Spike Matching).</p
<p>ROC curves of the APPCI, FI, APRI, GPI, and APGA noninvasive models in all study subjects.</p
<p>The classification rate and ROC values with and without feature selection.</p
<p>Comparison between ROC curves obtained with the marginal and integrated model.</p
ROC curves of the PR (a) and CR (b) model for the best and worst training (solid) and the validation...
<p>ROC curves for the two models of the development set using leave-one-out cross-validation (LOOCV)...
ROC curves for the mortality model, using test data (AUC values are indicated on the graph).</p
<p>ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p
ROC curves of the methods with different features for representing images and different classifiers....
<p>ROC curve for the best model found on the reduced feature set (replication).</p
<p>ROC curve for the best model found on the reduced feature set (discovery).</p
ROC curves for the top performing model compared to individual feature predictions.</p
<p>ROC curve for logistic regression, the best model found on the reduced feature set (discovery).</...
<p>ROC Curves with (+) or without (−) boundary detection (BD) and model fitness check (MFC).</p
ROC curves for logistic regression models for each outcome, using penalised regression of full paren...
<p>ROC Curve of different classification methods (SVM only, GA+SVM, GA+SVM+Post Spike Matching).</p
<p>ROC curves of the APPCI, FI, APRI, GPI, and APGA noninvasive models in all study subjects.</p
<p>The classification rate and ROC values with and without feature selection.</p
<p>Comparison between ROC curves obtained with the marginal and integrated model.</p
ROC curves of the PR (a) and CR (b) model for the best and worst training (solid) and the validation...
<p>ROC curves for the two models of the development set using leave-one-out cross-validation (LOOCV)...
ROC curves for the mortality model, using test data (AUC values are indicated on the graph).</p
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