<p>Based on the L1-regularized logistic regression model with six proteins, a receiver operating characteristic (ROC) curve yields an area under the curve (AUC) of 0.87. The color at a position along the curve is indicative of the specificity, and sensitivity can be gauged by looking at the color at the corresponding height along the left, vertical axis.</p
<p>Receiver operating characteristic curve (ROC) shows that the areas under ROC are approximately 0....
<p>Receiver-operating characteristic (ROC) curve for factors in predicting high ABI (*P<0.05). BMI, ...
<p>Receiver operating characteristic (ROC) curve indicating specificity and sensitivity of the risk ...
<p>Sensitivity and specificity values were obtained for increasing classification thresholds to prod...
<p>The area under the ROC (AUC) = 0.997 (95% confidence interval [CI] 0.991 to 1.000, <i>P</i><0.001...
<p>Receiver Operating Characteristic curve (ROC) curve associated with the logistic regression model...
<p>Note: the threshold at fixed specificity/sensitivity achieved by doctors are used to calculate th...
<p>Receiver operating characteristic (ROC) curves and corresponding areas under the curve (AUCs) com...
<p>The area under the curve (AUC) is 0.76, suggesting a strong ability to discriminate between true ...
<p>Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) values for train...
<p>Receiver operating characteristic (ROC) curves are a widely accepted indicator of diagnostic util...
<p>This figure shows the performance of the logistic regression model with the four predictive marke...
<p>The curve describes the tradeoff between sensitivity and specificity at different thresholds for ...
The diagonal grey line represents classifier models that randomly assign compounds to bioactivity cl...
ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation c...
<p>Receiver operating characteristic curve (ROC) shows that the areas under ROC are approximately 0....
<p>Receiver-operating characteristic (ROC) curve for factors in predicting high ABI (*P<0.05). BMI, ...
<p>Receiver operating characteristic (ROC) curve indicating specificity and sensitivity of the risk ...
<p>Sensitivity and specificity values were obtained for increasing classification thresholds to prod...
<p>The area under the ROC (AUC) = 0.997 (95% confidence interval [CI] 0.991 to 1.000, <i>P</i><0.001...
<p>Receiver Operating Characteristic curve (ROC) curve associated with the logistic regression model...
<p>Note: the threshold at fixed specificity/sensitivity achieved by doctors are used to calculate th...
<p>Receiver operating characteristic (ROC) curves and corresponding areas under the curve (AUCs) com...
<p>The area under the curve (AUC) is 0.76, suggesting a strong ability to discriminate between true ...
<p>Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) values for train...
<p>Receiver operating characteristic (ROC) curves are a widely accepted indicator of diagnostic util...
<p>This figure shows the performance of the logistic regression model with the four predictive marke...
<p>The curve describes the tradeoff between sensitivity and specificity at different thresholds for ...
The diagonal grey line represents classifier models that randomly assign compounds to bioactivity cl...
ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation c...
<p>Receiver operating characteristic curve (ROC) shows that the areas under ROC are approximately 0....
<p>Receiver-operating characteristic (ROC) curve for factors in predicting high ABI (*P<0.05). BMI, ...
<p>Receiver operating characteristic (ROC) curve indicating specificity and sensitivity of the risk ...