Fig. 8 | Scientific Reports

Fig. 8

From: Integrated machine learning identifies biomarkers for bilirubin-induced Alzheimer’s disease-like lesions in neonates and adults

Fig. 8

Construction and validation of a nomogram model for AD diagnosis (A) ROC curves of C4A, FSD2, HLA-DRB4, and FCGBP. (B) Nomogram integrating diagnostic markers for AD; each variable corresponds to a score, and the total score is obtained by summing across variables. (C) ROC curve demonstrating the diagnostic performance of the nomogram. (D) Calibration curve assessing the predictive accuracy of the nomogram. (E) Decision curve analysis (DCA) evaluating the clinical utility of the nomogram. (F) Expression levels and ROC curves of C4A, FSD2, HLA-DRB4, and FCGBP in the GSE33000 dataset.

Back to article page