Machine learning method for predicting glioma mutations shows promise for personalized treatment

Representative case of the independent internal patient cohort shows a 54-year-old male patient who suffered from an IDH-mutated oligodendroglioma WHO grade 2 that was correctly classified by all algorithms. Credit: Cancers (2024). DOI: 10.3390/cancers16061102 Machine learning (ML) methods can quickly and accurately diagnose mutations in gliomas—primary brain tumors. This is shown by a recent study by Karl Landsteiner University of Health Sciences (KL Krems). In this study, published in Cancers, data from physio-metabolic magnetic resonance images were analyzed to identify mutations in a metabolic gene using ML. Mutations of this Read More