Predicting Histological Grade In Pediatric Glioma Using Multiparametric Radiomics And Conventional Mri Features

This study aims to develop a machine learning model that combines traditional imaging features and radiomics features to improve the prediction of histological grade in pediatric gliomas. The model was trained using multiparametric MRI and showed promising results in accurately grading tumors. The TOP 10 radiomics features were identified as the most important in this study.