The analyses also highlight four significant advances [54,55,63,93] that focus on the use of radiomic features and machine-learning methods to predict IDH1-mutation status in gliomas, and five MGMT-focused articles [32,36,44,62,80] that utilize radiomics to predict the methylation status of the MGMT gene promoter in glioblastoma multiforme patients. The gene discussed is MGMT; the disease is glioma.