A Methylation Diagnostic Model Based on Random Forests and Neural Networks for Asthma Identification

Figure 6

Two datasets determine neural network classification efficiency. (a) ROC result of GSE137716 dataset. (b) ROC result of GSE40576. The points marked on ROC curve are the optimal threshold points, and the values in parentheses indicate sensitivity and specificity. The AUC value was the Area Under ROC Curve, -axis was the specificity, and -axis was the sensitivity. The optimal threshold was marked at the inflection point, and sensitivity and specificity were listed in parentheses.

(a)

(b)