Using Machine Learning to Predict Brain Tumor Progression - Neuroscience News

Summary: Combining machine learning technology with neuroimaging data, clinicians will be better able to fully analyze a patient's glioblastoma brain tumor and predict cancer progression. Researchers at the University of Waterloo have created a computational model to predict the growth of deadly brain tumors more accurately. Glioblastoma multiforme (GBM) is a brain cancer with an average survival rate of only one year. It is difficult to treat due to its extremely dense core, rapid growth, and location in the brain. Estimating these tumors' diffusivity and proliferation rate is useful for clinicians, but that information is hard to predict for an individual patient quickly and accurately.