Often, the tumors are predecessors to cancers, and the survival rates are very low. So, early detection and classification of tumors can save a lot of lives. IoMT enabled CAD system plays a vital role ...

Brain cancer detection and localization based on Explainable Artificial Intelligence (X-AI) technology have the potential to be a valuable tool for the accurate and efficient diagnosis of brain cancer ...

New machine learning (ML)-based tool developed by researchers helps detect cancer-causing tumors in the brain and spinal cord. ‘aGBMDriver' (GlioBlastoma Mutiforme Drivers), the machine learning ...

Multiclass machine learning methods were used to analyze and classify brain tumors using physiological data from magnetic resonance imaging. The results were then compared with classifications ...

Diffusion MRI and machine learning models classify childhood brain tumours. The CNN demonstrated good generalization capability, scoring an accuracy of 91.95% on the external test data. The results ...

A new machine learning approach classifies a common type of brain tumor into low or high grades with almost 98% accuracy, researchers report in the journal IEEE Access.

Brain tumors are growths of abnormal cells in the brain. It is one of the most dangerous type of cancer and requires precise classification for accurate diagnosis and treatment ( 1 Trusted Source ...

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.