<p>Area under ROC curve (AUC) = 0.843 <sup>without DZM</sup>, 0.886<sup> with DZM</sup> * Case classification with adjusted cut –off probability = 0.19 at (Sensitivity = 0.81, Specificity = 0.80).</p
Logistic regression is often used to find a linear combination of covariates which best discriminate...
<p>Logistic Regression Model for Reduced FA in Centrum Semiovale (ROC Curve: AUC = 0.678).</p
The red point on the curve minimized the Euclidian distance between the ROC curve and the upper left...
<p>The Solid line represents DZM on its own at AUC = ∼66%, the dotted line shows the model with DZM ...
<p>(A) Parameters of each model. (B) The ROC curve of a model consisting of rs9351963+MMC+ Amrubicin...
<p>This figure shows the performance of the logistic regression model with the four predictive marke...
<p>Based on the L1-regularized logistic regression model with six proteins, a receiver operating cha...
<p>(A) ROC curves for each regression model. The diagonal reference line indicates performance accor...
<p>The area under the ROC (AUC) = 0.997 (95% confidence interval [CI] 0.991 to 1.000, <i>P</i><0.001...
<p>The area under the curve for ADMA levels in predicting adverse events was 0.767 (95% confidence i...
<p>The areas under the ROC curves (AUC values) are reported in <a href="http://www.ploscompbiol.org/...
The curves represent the average curves for the 20 ANN and 20 logistic models. The area under the RO...
<p>The longitudinal axis represents sensitivity to predict the probability of POTS. The transversal ...
We compute the area under the curve (AUC) for each model and each cohort, where a perfect classifier...
<p>The ROC curve is based upon a logistic regression model for CCR7+ Treg predicting BOS outcome, wh...
Logistic regression is often used to find a linear combination of covariates which best discriminate...
<p>Logistic Regression Model for Reduced FA in Centrum Semiovale (ROC Curve: AUC = 0.678).</p
The red point on the curve minimized the Euclidian distance between the ROC curve and the upper left...
<p>The Solid line represents DZM on its own at AUC = ∼66%, the dotted line shows the model with DZM ...
<p>(A) Parameters of each model. (B) The ROC curve of a model consisting of rs9351963+MMC+ Amrubicin...
<p>This figure shows the performance of the logistic regression model with the four predictive marke...
<p>Based on the L1-regularized logistic regression model with six proteins, a receiver operating cha...
<p>(A) ROC curves for each regression model. The diagonal reference line indicates performance accor...
<p>The area under the ROC (AUC) = 0.997 (95% confidence interval [CI] 0.991 to 1.000, <i>P</i><0.001...
<p>The area under the curve for ADMA levels in predicting adverse events was 0.767 (95% confidence i...
<p>The areas under the ROC curves (AUC values) are reported in <a href="http://www.ploscompbiol.org/...
The curves represent the average curves for the 20 ANN and 20 logistic models. The area under the RO...
<p>The longitudinal axis represents sensitivity to predict the probability of POTS. The transversal ...
We compute the area under the curve (AUC) for each model and each cohort, where a perfect classifier...
<p>The ROC curve is based upon a logistic regression model for CCR7+ Treg predicting BOS outcome, wh...
Logistic regression is often used to find a linear combination of covariates which best discriminate...
<p>Logistic Regression Model for Reduced FA in Centrum Semiovale (ROC Curve: AUC = 0.678).</p
The red point on the curve minimized the Euclidian distance between the ROC curve and the upper left...