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Found 3 papers, 2 papers with code
Transformer-based interpretable multi-modal data fusion for skin lesion classification
A lot of deep learning (DL) research these days is mainly focused on improving quantitative metrics regardless of other factors.
Attention-based Saliency Maps Improve Interpretability of Pneumothorax Classification
Conclusion: ViTs performed similarly to CNNs in CXR classification, and their attention-based saliency maps were more useful to radiologists and outperformed GradCAM.
A knee cannot have lung disease: out-of-distribution detection with in-distribution voting using the medical example of chest X-ray classification
The proposed IDV approach trained on ID (chest X-ray 14) and OOD data (IRMA and ImageNet) achieved, on average, 0. 999 OOD AUC across the three data sets, surpassing all other OOD detection methods.
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