Improving Brain Tumor Detection with Deep Learning and Explainable AI
New deep learning frameworks for brain tumor detection are increasingly utilizing stratified patient-wise cross-validation and quantitative explainability (XAI) metrics to bridge the gap between algorithmic performance and clinical reliability. By integrating architectures like InceptionV3 with rigorous testing on independent datasets, researchers are addressing critical hurdles in medical AI, specifically data scarcity and the “black box” … Read more
