Background: Intracranial aneurysm (IA) is a potentially devastating cerebrovascular disease, and its rupture leads to subarachnoid hemorrhage with high mortality and disability rates. This study aimed to predict the potential biomarkers of ruptured intracranial aneurysms (RIAs) and explore the correlation between RIAs and immune infiltration through artificial neural networks and bioinformatics analysis.Method: Three RIA gene microarray data sets were obtained from the gene expression profile (GEO) database, with GSE13353 and GSE36791 as the training sets and GSE54083 as the validation set. Differentially expressed genes (DEGs) were obtained after the analysis. The Kyoto Encyclopedia of Genes and Genomes, Gene Ontology, and Metascape databases were used for functional enrichment analysis. A random forest tree was used to screen for disease signature genes, while a neural network model was built afterward. The accuracy was also confirmed in the validation set. Finally, immune cell infiltration in the unruptured IAsand RIAs groups was analyzed using CIBERSORT.Results: A total of 27 DEGs were identified by the analysis, 1 of which was a downregulated gene and 26 were upregulated genes. The functional enrichment associated with RIAs was closely related to inflammation and immune function. Hexokinase 3, matrix metalloproteinase 9, CST7, NCF2, and uridine phosphorylase 1 were disease signature genes for RIAs and could be used as potential markers for predicting RIAs. The numbers of CD8+ T cells, CD4+ memory T cells, activated natural killer cells, macrophages M0, and neutrophils were high in the RIA group in immune cell infiltration analysis.Conclusion: The analysis revealed disease signature genes and immune cell infiltration types that predicted RIAs and had important effects on inflammatory and immune responses.