Endoscopies were performed with various generations of Olympus scopes (GIF-Q160, GIF-Q160Z ... Further, we computed the receiver operating characteristic (ROC) curves and the AUC. The best performing ...

The area under the ROC curve (AUC) is a natural measure for overall assessment of a classifier based on the ROC curve. We discuss a class of concave functions for AUC maximization in which a ...

from sklearn.metrics import f1_score,precision_score,recall_score,roc_auc_score,roc_curve,confusion_matrix,accuracy_score,log_loss img_width = 224 #parameter：the width of image img_height = 224 ...

Results Model training and internal validation were performed on 5054 WSIs of 2080 patients resulting in an area under the curve-receiver operating characteristic (AUC-ROC) of 0.98 (SD=0.004) and ...

To address this need, we introduce Conditional Prediction ROC (CP-ROC) bands, offering uncertainty quantification for ROC curves and robustness to distributional shifts in test data. Although ...

The ROC results were described by the area under the curve (AUC) statistic and associated p values computed by the method of DeLong. For all analyses, a two-tailed p value <0.05 was considered ...

The hyperparameters that generated the largest area under the receiver operator characteristic curve (AUC) were chosen. See online supplemental table 2 for details of the selected hyperparameter ...

Results The algorithm’s area under the receiver operating characteristic curve (AUROC ... we used the metrics of area under the curve (AUC), sensitivity, specificity and accuracy. The optimal ...