Brain Cancer

Researchers have developed an AI model that analyzes sequences of brain scans to accurately predict tumor recurrence in children with gliomas. By applying a method called temporal learning, the model interprets subtle changes in MR images taken post-treatment over time. The study found that using multiple images significantly outperforms traditional single-scan analysis, reaching prediction accuracy rates as high as 89%.