<p>(A) ROC curve of the 349-gene predictive model in training set (200 samples, AUC = 0.826; <i>p<</i>0.001. (B) ROC curve of the 349-gene predictive model in the testing set (122 samples, AUC = 0.702; <i>p</i> = 0.022). (C) ROC curve of the 18-gene de-correlated predictive model in the training set (200 samples, AUC = 0.775; <i>p</i><0.001. (D) ROC curve of the 18-gene de-correlated predictive model in the testing set (122 samples, AUC = 0.614; <i>p</i> = 0.197).</p
<p>ROC curves of the residual variation intolerance scores' capacity to predict the corresponding in...
Model A (blue line) incorporates classical risk factors and five GWAS-identified SNPs, whereas model...
<p><b>Copyright information:</b></p><p>Taken from "Prediction potential of candidate biomarker sets ...
<p>(a) first ROC: Class 1 – four-fold NP differentially over-expressed genes compared to ES; Class 0...
(A) Performance of the model in the training set, which showed an AUC value of 0.768, an optimal cut...
<p>Solid line (<sup>____</sup>) represents ROC curve for simulation model based on 6 genotyped SNPs ...
<p>The solid curve is the ROC curve for the prediction model established on the basis of the trainin...
<p>(a) shows genes contained in the integrated BRCA pathway, (c) shows genes contained in the GBM KE...
<p>In each figure, the solid (<i>blue</i>) curve corresponds to the cross validation test on the sam...
<p>In (A) <i>AKY</i> and (B) <i>BBJ</i>, case samples with PSA 1–10 ng/ml and all the control sample...
ROC curves are plotted using 10 randomly selected training and testing data sets using 80%, and 20% ...
<p>(A) The grouping variable predictions for four patient subgroups (RA group: blue line, MA group: ...
<p>(A) ROC curves for Gram-negative dataset. (B) ROC curves for Gram-positive dataset. (C) ROC curve...
<p>ROC curves derived from the univariate logistic analysis corresponding to total cfDNA (AUC = 0.85...
<p>A: one covariate model ROC curves based on the risk score of <i>miR-195</i>; B: two covariate mod...
<p>ROC curves of the residual variation intolerance scores' capacity to predict the corresponding in...
Model A (blue line) incorporates classical risk factors and five GWAS-identified SNPs, whereas model...
<p><b>Copyright information:</b></p><p>Taken from "Prediction potential of candidate biomarker sets ...
<p>(a) first ROC: Class 1 – four-fold NP differentially over-expressed genes compared to ES; Class 0...
(A) Performance of the model in the training set, which showed an AUC value of 0.768, an optimal cut...
<p>Solid line (<sup>____</sup>) represents ROC curve for simulation model based on 6 genotyped SNPs ...
<p>The solid curve is the ROC curve for the prediction model established on the basis of the trainin...
<p>(a) shows genes contained in the integrated BRCA pathway, (c) shows genes contained in the GBM KE...
<p>In each figure, the solid (<i>blue</i>) curve corresponds to the cross validation test on the sam...
<p>In (A) <i>AKY</i> and (B) <i>BBJ</i>, case samples with PSA 1–10 ng/ml and all the control sample...
ROC curves are plotted using 10 randomly selected training and testing data sets using 80%, and 20% ...
<p>(A) The grouping variable predictions for four patient subgroups (RA group: blue line, MA group: ...
<p>(A) ROC curves for Gram-negative dataset. (B) ROC curves for Gram-positive dataset. (C) ROC curve...
<p>ROC curves derived from the univariate logistic analysis corresponding to total cfDNA (AUC = 0.85...
<p>A: one covariate model ROC curves based on the risk score of <i>miR-195</i>; B: two covariate mod...
<p>ROC curves of the residual variation intolerance scores' capacity to predict the corresponding in...
Model A (blue line) incorporates classical risk factors and five GWAS-identified SNPs, whereas model...
<p><b>Copyright information:</b></p><p>Taken from "Prediction potential of candidate biomarker sets ...