Fig. 3 | Scientific Reports

Fig. 3

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

Fig. 3

Identification of potential diagnostic biomarkers. (A) Venn diagram of candidate variables screened by KEGG gene sets and module genes. (B) Selection of diagnostic markers using the RF algorithm. (C) Selection of diagnostic markers using the SVM-RFE algorithm. (D) Venn diagram showing the overlap of variables identified by ROC, RF, and SVM-RFE analyses. (E, F) Expression levels and ROC curves of BBC3 and MAP3kK10. (G) Expression levels and ROC curves of BBC3 and MAP3K10 in the GSE15222 dataset. (H) KEGG pathway enrichment of candidate genes. (I) Correlation analysis between BBC3, MAP3K10, and enriched pathways.

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