Brain Cancer

Brain cancer research intensely focuses on improving diagnosis, treatment planning, and survival prediction. Current efforts leverage advanced machine learning techniques, particularly deep learning models like convolutional neural networks (CNNs) and vision transformers, to analyze medical images (primarily MRI scans) for accurate tumor segmentation and classification, and to predict recurrence location and patient survival. These computational approaches aim to enhance the objectivity and efficiency of clinical decision-making, potentially leading to improved patient outcomes by integrating multi-modal data (radiological, pathological, genomic, and demographic) and addressing challenges posed by incomplete datasets. However, some studies suggest limitations in predicting certain genetic markers directly from MRI scans.