A model that first performed automated tumor segmentation and subsequently used both radiomics and deep-learning derived features was able to predict the IDH mutational status of patients diagnosed with gliomas with an accuracy of 78.8% and 93.8% on internal and external test sets, respectively. This evidence concerns the gene IDH1 and central nervous system cancer.