The new machine learning tool prioritizes driver mutations in brain tumor (glioblastoma) and assists in identifying therapeutic targets.

The University of Pennsylvania Perelman School of Medicine joined with Intel Labs to conduct a research study to improve brain tumor detection by using a kind of machine learning called Federated ML.

Using data from 71 institutions across six continents, the project demonstrated the ability to improve brain tumor detection by 33%.

Researchers used a deep learning model to turn the MRI data into patient-specific parameter estimates that inform a predictive model for brain tumor growth.

Research shows that CNNs trained on camouflage detection improve brain tumor classification in MRI scans, highlighting the potential of unconventional training.

They're using machine learning to fully analyze a patient's tumour, to better predict cancer progression. Researchers analyzed two sets of MRIs from each of five anonymous patients suffering from GBM.

Then, using a machine learning approach, they developed a computer program to classify the brain tumor type based solely on the ctDNA.