Causally Constrained and Anatomically Grounded Interpretability in Deep Learning for Chest Radiograph Diagnosis
Although deep learning systems have proved to have high potential in classifying chest radiographs, their low level of transparency still limits their widespread clinical use on a regular basis. Most current models produce visual explanations that are generated post-prediction, and frequently point out regions that do...