The datasets regarding CP were downloaded from the Gene Expression Omnibus (GEO) database. The differential expression analysis was performed to identify the differentially expressed genes (DEGs). Afterward, the genes related to AD were downloaded from the DisGeNET database. The intersection between DEGs in CP and AD-related genes was defined as the crosstalk genes between CP and AD. The Boruta algorithm was used for feature selection of crosstalk genes, and thus the representative crosstalk genes were obtained. In addition, the support vector machine (SVM) model was constructed by using the python and scikit-learn algorithm. The crosstalk genes-TFs network and crosstalk genes-DEP (differentially expressed pathways) network were constructed. Finally, the overlapping genes between crosstalk genes and CP-related genes from DisGeNET were obtained and identified to be the most critical crosstalk genes.