<p>A ROC curve plots the true positive rate (i.e., sensitivity) against the false positive rate (i.e., 1 − specificity). Shown are the ROC curves for CONC using all features, two of the top single features, and ESTScan. The diagonal line indicates random prediction.</p
<p>In each figure, the solid (<i>blue</i>) curve corresponds to the cross validation test on the sam...
<p>(a) ROGER logistic scoring function, (b) Default RosettaDock score, (c) the whole protein-RNA ben...
<p>The longitudinal axis represents sensitivity to predict the probability of POTS. The transversal ...
<p>ROC plot depicts a relative trade-off between true positive rate and false positive rate of the p...
<p>The blue line indicates the prediction scenario using only clinical variables (hippocampal sclero...
<p>The curve presents the true positive rate (or sensitivity) in function of false positive rate for...
<p>ROC curves (a plot of true positive rate (Sensitivity) against false positive rate (1-Specificity...
<p>Under each scenario, 25 datasets were simulated. Lighter lines indicate the ROC curve for a parti...
<p>Panel A gives the ROC curves at each possible control of false positive rate, while panel B only ...
<p>FPR represents the false positive rate, and TPR is the true positive rate. The ROC curve is close...
Where, X-axis (1-specificity) represents the false positives in decoys. Y-axis (sensitivity) represe...
<p><b>Copyright information:</b></p><p>Taken from "Human microRNA prediction through a probabilistic...
<p>The x-axis is the false- positive rate, 1 –specificity; the y-axis is the true- positive rate, se...
<p>This translated into a sensitivity = 88% and specificity = 72% for discriminating between progres...
<p>Sensitivity and specificity was maximized at a sensitivity of 0.858 and specificity of 0.623.</p
<p>In each figure, the solid (<i>blue</i>) curve corresponds to the cross validation test on the sam...
<p>(a) ROGER logistic scoring function, (b) Default RosettaDock score, (c) the whole protein-RNA ben...
<p>The longitudinal axis represents sensitivity to predict the probability of POTS. The transversal ...
<p>ROC plot depicts a relative trade-off between true positive rate and false positive rate of the p...
<p>The blue line indicates the prediction scenario using only clinical variables (hippocampal sclero...
<p>The curve presents the true positive rate (or sensitivity) in function of false positive rate for...
<p>ROC curves (a plot of true positive rate (Sensitivity) against false positive rate (1-Specificity...
<p>Under each scenario, 25 datasets were simulated. Lighter lines indicate the ROC curve for a parti...
<p>Panel A gives the ROC curves at each possible control of false positive rate, while panel B only ...
<p>FPR represents the false positive rate, and TPR is the true positive rate. The ROC curve is close...
Where, X-axis (1-specificity) represents the false positives in decoys. Y-axis (sensitivity) represe...
<p><b>Copyright information:</b></p><p>Taken from "Human microRNA prediction through a probabilistic...
<p>The x-axis is the false- positive rate, 1 –specificity; the y-axis is the true- positive rate, se...
<p>This translated into a sensitivity = 88% and specificity = 72% for discriminating between progres...
<p>Sensitivity and specificity was maximized at a sensitivity of 0.858 and specificity of 0.623.</p
<p>In each figure, the solid (<i>blue</i>) curve corresponds to the cross validation test on the sam...
<p>(a) ROGER logistic scoring function, (b) Default RosettaDock score, (c) the whole protein-RNA ben...
<p>The longitudinal axis represents sensitivity to predict the probability of POTS. The transversal ...
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