Multimodal Cancer Classification Using a SwinR Transformer Cross-Attention and Contrastive Learning
Deep learning models are designed to process complex medical images, allowing physicians to more accurately identify and classify cancerous cells. There precision and speed, are both crucial in real clinical settings. This paper presents an enhanced SwinR Transformer based framework that incorporates hierarchical featu...