IDH1 and glioma: in a heterogeneous cohort of gliomas [n = 100 (grade-I I = 11; grade-3 = 8 and grade IV: 81)] used MRI-based radiomic features to predict IDH1 Mutation Status in Gliomas using a gradient tree boost machine learning classifier.