The efficacy of different ANN topologies are evaluated for their predictive accuracy.
Accordingly, different combinations of new biomarkers and T-tau were evaluated for their diagnostic accuracy.
Numerous classifiers have been proposed and evaluated for their comparative accuracy in correctly identifying cancer tumors [4] [7].
The following new biomarkers were evaluated for their diagnostic accuracy: total transferrin by Western blot (T-Tf (WB)) and ELISA (T-Tf (ELISA)) techniques, Tf-1, Tf-β2, and iron saturation of Tf (59Fe-Tf).
The expression ratios of six different combinations between the 2 upregulated and 3 downregulated miRNAs were then evaluated for their diagnostic accuracy using ROC analysis).
Thus, the recent MSA programs [ 18, 20] capable of aligning large quantities of 16S rRNA sequences must be evaluated for their alignment accuracy, as currently performed for Muscle, T-COFFEE, MAFFT, Probcons, and the Clustalw MSA programs for protein sequences [ 25, 26].
The tested models, i.e., the Cox regression model containing the conventional markers alone and the three different feature selection models (the Lasso and Ridge regressions and the C-index boosting algorithm) were evaluated for their predictive accuracies (generalizabilities) using the deviance from the null model and iRBS.
The methylation levels and percentages of LINE-1 loci were evaluated for their sensitivity, specificity, and accuracy for the prediction of postmolar GTN.
Although T2D risk assessment tools based on clinical risk factors typically are quite accurate, genetic tests, both alone and in combination with clinical risk factors, have been evaluated for their ability to improve the accuracy of T2D risk prediction.
