A Comparison of Machine Learning Models for Survival Prediction of Patients with Glioma Using Radiomic Features from MRI Scans.

 Glioma is a primary, malignant, highly aggressive brain tumor, with patients having an average life expectancy of 14 to 16 months after diagnosis. Magnetic resonance imaging (MRI) scans of these patients can be used to extract and analyze quantifiable features with potential clinical significance. We hypothesize that there is a correlation between radiomic features extracted from MRI scans and survival.