Fig. 9

Diagnostic and validation of GSE135917 and friends analysis. (A) ROC curve of RiskScore in dataset GSE135917. (B) Nomogram of Model Genes in dataset GSE135917 in OSA diagnostic model. (C, D) Calibration Curve plot (C) and decision curve analysis (DCA) plot (D) of the OSA diagnostic Model based on the Model Genes in dataset GSE135917. (E) Box plot of functional similarity (Friends) analysis results of Model Genes. The ordinate of the decision curve analysis (DCA) plot is the net benefit, and the abscissa is the Probability Threshold or Threshold Probability. The AUC of the ROC curve is generally between 0.5 and 1. The closer the AUC is to 1, the better the diagnostic performance. High accuracy is achieved when AUC is above 0.9. ROC Receiver Operating Characteristic, AUC Area Under the Curve, DCA Decision Curve Analysis, TPR True Positive Rate, FPR False Positive Rate.