Pediatric cancer recurrence is a pressing concern for families navigating the complexities of childhood cancers, particularly soft tissue tumors such as pediatric gliomas.Recent advances in AI predicting cancer relapse reveal that innovative algorithms can significantly enhance the accuracy of relapse risk assessment compared to traditional methods.