WSI Classification

Whole slide image (WSI) classification aims to automatically diagnose diseases from high-resolution digital pathology scans, improving efficiency and accuracy in healthcare. Current research focuses on developing robust and interpretable models, often employing deep learning architectures like transformers and graph neural networks, and incorporating multimodal data (e.g., combining H&E and IHC staining) or leveraging techniques like multi-instance learning to handle the inherent variability within WSIs. These advancements hold significant promise for improving cancer diagnosis and prognosis, accelerating research, and potentially reducing the workload on pathologists.