The lack of interpretability in the field of medical image analysis has significant ethical and
legal implications. Existing interpretable methods in this domain encounter several …

Concept-based learning enhances prediction accuracy and interpretability by leveraging
high-level, human-understandable concepts. However, existing CBL frameworks do not …

Concept Bottleneck Models (CBM) map images to human-interpretable concepts before
making class predictions. Recent approaches automate CBM construction by prompting …