<p>Abbreviations: ASD55, the genes in a classifier developed on P1 with 55 genes listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049475#pone.0049475.s008" target="_blank">Table S4</a>; AUC, area under the receiver operating characteristic curve.</p
<p>For all datasets for which predictions with all three methods could be made, the AUC values obtai...
<p>The area under the receiver operating characteristic curve (AUC) for clinical characteristics (ag...
<p>Performance for binary classifiers under each organism (AUROC = area under the receiver operator ...
<p>Receiver operating characteristic (ROC) curve analysis was performed to evaluate the prediction a...
<p>The dendrogram and heatmap on top show hierarchical clustering (average linkage) of the 99 sample...
<p>The results in the first row show the AUC values for comparing against OMIM’s gene–disease associ...
Performance metrics (r2, AUC) and their standard deviations are computed on an independent test set....
<p>AUC<sup>a</sup>: area under the receiver operating characteristic curves.</p><p>SEER<sup>b</sup>:...
<p>AUC<sup>a</sup>: area under the receiver operating characteristic curves.</p><p>CMU-SO<sup>b</sup...
<p>A highest area under curves (AUC) value of 0.5 indicates no predictive, while an AUC of 1 indicat...
<p>Performance (ROC AUC) of classifiers on each tissue-specific enhancer prediction task (Step 2).</...
<p>Abbreviation used: AUC, the least area under the curve; A, nodules within the 7 to 10 millimeters...
<p><b>(A)</b> AUC of the three algorithms. AUC measures the area under the ROC curves. <b>(B)</b> Pe...
<p>Area Under the Curve (AUC) was obtained from the ROC curves of 9 predictors: AUC cannot be comput...
<p>For each predictor, the AUC obtained in the training and validation sets, as well as the 95% Conf...
<p>For all datasets for which predictions with all three methods could be made, the AUC values obtai...
<p>The area under the receiver operating characteristic curve (AUC) for clinical characteristics (ag...
<p>Performance for binary classifiers under each organism (AUROC = area under the receiver operator ...
<p>Receiver operating characteristic (ROC) curve analysis was performed to evaluate the prediction a...
<p>The dendrogram and heatmap on top show hierarchical clustering (average linkage) of the 99 sample...
<p>The results in the first row show the AUC values for comparing against OMIM’s gene–disease associ...
Performance metrics (r2, AUC) and their standard deviations are computed on an independent test set....
<p>AUC<sup>a</sup>: area under the receiver operating characteristic curves.</p><p>SEER<sup>b</sup>:...
<p>AUC<sup>a</sup>: area under the receiver operating characteristic curves.</p><p>CMU-SO<sup>b</sup...
<p>A highest area under curves (AUC) value of 0.5 indicates no predictive, while an AUC of 1 indicat...
<p>Performance (ROC AUC) of classifiers on each tissue-specific enhancer prediction task (Step 2).</...
<p>Abbreviation used: AUC, the least area under the curve; A, nodules within the 7 to 10 millimeters...
<p><b>(A)</b> AUC of the three algorithms. AUC measures the area under the ROC curves. <b>(B)</b> Pe...
<p>Area Under the Curve (AUC) was obtained from the ROC curves of 9 predictors: AUC cannot be comput...
<p>For each predictor, the AUC obtained in the training and validation sets, as well as the 95% Conf...
<p>For all datasets for which predictions with all three methods could be made, the AUC values obtai...
<p>The area under the receiver operating characteristic curve (AUC) for clinical characteristics (ag...
<p>Performance for binary classifiers under each organism (AUROC = area under the receiver operator ...