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cs.CV2025
Hybrid Explanation-Guided Learning for Transformer-Based Chest X-Ray Diagnosis
Shelley Zixin Shu, Haozhe Luo, Alexander Poellinger +1
Transformer-based deep learning models have demonstrated exceptional performance in medical imaging by leveraging attention mechanisms for feature representation and interpretabili…
cs.CV2025
On the Interplay of Human-AI Alignment,Fairness, and Performance Trade-offs in Medical Imaging
Haozhe Luo, Ziyu Zhou, Zixin Shu +3
Deep neural networks excel in medical imaging but remain prone to biases, leading to fairness gaps across demographic groups. We provide the first systematic exploration of Human-A…
cs.CV2024
DWARF: Disease-weighted network for attention map refinement
Haozhe Luo, Aurélie Pahud de Mortanges, Oana Inel +2
The interpretability of deep learning is crucial for evaluating the reliability of medical imaging models and reducing the risks of inaccurate patient recommendations. This study a…