We screened out four sets of high-order radiomics feature clusters based on T2 FLAIR through supervised machine learning and established four predictive models for immunohistochemical biomarker prediction using the positive/negative pathological results of Ki-67, S-100, vimentin and CD34 as labels in gliomas patients. Here, S100B is linked to glioma.