MedMamba Explained: The Revolutionary Vision Mamba for Medical Image Classification The Paradigm Shift in Medical AI Since the emergence of deep learning, Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) have dominated medical image classification. Yet these architectures face fundamental limitations: CNNs struggle with long-range dependencies due to constrained receptive fields ViTs suffer from quadratic complexity (O(N²)) in self-attention mechanisms Hybrid models increase accuracy but fail to resolve computational bottlenecks The healthcare sector faces critical challenges: “Medical imaging data volume grows 35% annually (Radiology Business Journal, 2025), yet diagnostic errors still account for 10% of patient adverse events (WHO Report).” …