Current Status and Quality of Machine Learning-Based Radiomics Studies for Glioma Grading: A Systematic Review.

The current studies are promising but very heterogeneous in design with high variation in the radiomics software, the number of extracted features, the number of selected features, and machine learning models. All of the studies were retrospective in design; many are based on small datasets and/or suffer from class imbalance and lack of external validation data-sets.