This study evaluated radiomics-based machine learning models for noninvasive prediction of isocitrate dehydrogenase mutation status and overall survival in glioma patients.<h4>Methods</h4>From T2-weighted MRI scans of 638 gliomas (213 from a local institution (discovery), 425 from a public dataset (validation)), 1,820 radiomics features were extracted. The gene discussed is IDH3A; the disease is central nervous system cancer.