Clustering-constrained Attention Multiple Instance Learning (CLAM) is a method for classifying whole slide histopathology images using only slide-level labels without requiring region-of-interest annotations. The pipeline includes segmentation, patching, feature extraction, and attention-based training with instance-level clustering to identify diagnostically relevant sub-regions. It has been validated across multiple datasets including TCGA data and smartphone microscopy images.