Fig. 7

Identification of potential diagnostic biomarkers for CKD-related CAVD by the machine learning methods. A The venn diagram showing the 17 overlapping genes of CKD-associated secretory proteins, CAVD DEGs and CAVD key modules genes. B, C The minimum (B) and lambda values (C) of diagnostic biomarkers (n = 8) were identified by the LASSO logistic regression algorithm. D The RF algorithm presenting the MeanDecreaseGini of the 17 genes in CAVD and 6 biomarkers with the score more than 2.0 were selected. E The venn diagram displaying two common genes between LASSO and RF algorithms, which were identified as the hub genes in CKD-related CAVD. CKD chronic kidney disease, CAVD calcific aortic valve disease, DEGs differentially expressed genes, LASSO least absolute shrinkage and selection operator, RF random forest