*<p>Model A: Five features selected by backwards elimination: (FeretY_ave, MaxDiameter_ave, Elongation_ave, Slope_ave, ODKurtosis_ave).</p>**<p>Model B: Five features (SumOD_sd, MaxDiameter_sd, TSD_sd, TEntropy_sd, No.MedDensityObjects_sd), selected after competition among all models with ≤5 covariates based on leave-one-out AUC.</p
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
<p>(A) Joint distribution of the individual risk scores for the 1,027 patients according to two pred...
*<p>Model A: 5 features selected by backwards elimination (FeretY_ave, MaxDiameter_ave, Elongation_a...
<p>(A) A bar plot describing the predicted AUC obtained over the combined datasets of the same cance...
<p>Fitted multifeature scores were generated for each nucleus from a logistic regression model compa...
<p>AUC<sup>a</sup>: area under the receiver operating characteristic curves.</p><p>SEER<sup>b</sup>:...
<p>SNPs were divided into 6 models based on MAF or haplotype. AUC (A) and TPR (B) were calculated us...
<p>Method: forward feature selection (likelihood ratios).</p><p>Nagelkerke R-squared: *0.574, <sup>°...
<p>Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) score plot for cancer ...
<p>The area under the curve (AUC) as an accuracy measure for discrimination between high-grade and l...
<p>Two models were compared T2 and T2Tex using the metrics: TPR = Sensitivity, SPC = Specificity, PP...
Multidimensional scaling (MDS) plots showing dissimilarity of patients based on their gene expressio...
<p>Risk scores and ROC curves for the discriminating profiles are shown. (A) A 3- protein profile ba...
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
<p>(A) Joint distribution of the individual risk scores for the 1,027 patients according to two pred...
*<p>Model A: 5 features selected by backwards elimination (FeretY_ave, MaxDiameter_ave, Elongation_a...
<p>(A) A bar plot describing the predicted AUC obtained over the combined datasets of the same cance...
<p>Fitted multifeature scores were generated for each nucleus from a logistic regression model compa...
<p>AUC<sup>a</sup>: area under the receiver operating characteristic curves.</p><p>SEER<sup>b</sup>:...
<p>SNPs were divided into 6 models based on MAF or haplotype. AUC (A) and TPR (B) were calculated us...
<p>Method: forward feature selection (likelihood ratios).</p><p>Nagelkerke R-squared: *0.574, <sup>°...
<p>Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA) score plot for cancer ...
<p>The area under the curve (AUC) as an accuracy measure for discrimination between high-grade and l...
<p>Two models were compared T2 and T2Tex using the metrics: TPR = Sensitivity, SPC = Specificity, PP...
Multidimensional scaling (MDS) plots showing dissimilarity of patients based on their gene expressio...
<p>Risk scores and ROC curves for the discriminating profiles are shown. (A) A 3- protein profile ba...
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
OBJECTIVE: Two logistic regression models have been developed for the characterization of adnexal ma...
<p>(A) Joint distribution of the individual risk scores for the 1,027 patients according to two pred...