According to Chakrabarty, machine and deep learning approaches using MRI data could potentially automate the detection and classification of brain tumors.

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

Neural networks trained with a camouflage detection step show enhanced accuracy and sensitivity in identifying brain tumors from MRI scans, mimicking expert radiologists. Study: Deep learning and ...

A unique combination of explainable AI and repurposing animal camouflage detection algorithms can identify human brain cancer.

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.

The University of Pennsylvania and chipmaker Intel are forming a partnership to enable 29 heatlhcare and medical research institutions around the world to train artificial intelligence models to ...

A new study published in the Journal of Theoretical Biology demonstrates how AI deep learning can predict brain tumor progression for glioblastoma from medical images to accelerate precision medicine.

Current methods to diagnose brain cancer based on molecular information rely upon invasive surgical techniques to obtain tissue samples. A noninvasive way to make a diagnosis would be a game-changer ...