Machine Learning Method For Predicting Glioma Mutations Shows Promise For Personalized Treatment

A recent study by Karl Landsteiner University of Health Sciences (KL Krems) has shown that machine learning methods can accurately diagnose mutations in gliomas, the most common primary brain tumors. The study also highlights the need for consistent standards in obtaining physio-metabolic magnetic resonance images for routine clinical use.