Enhancing deep learning interpretability for hand-crafted feature-guided histologic image classification via weak-to-strong generalization

Our study elucidates the key HCFs that drive DL model predictions in histologic image classification. The findings demonstrate that integrating HCFs into DL model training via the WSG framework can enhance both the interpretability and the model's predictive performance, supporting their broader clinical adoption.