Our study demonstrated that KNN and Ensemble models exhibited the highest classification performance, with KNN achieving 92.59% accuracy, 100% precision, and an AUC of 0.90, making it the most reliable model in distinguishing IDH1-positive and IDH1-negative gliomas. This evidence concerns the gene IDH1 and central nervous system cancer.