<ul><li>Medical imaging, particularly X-ray analysis, often involves detecting multiple conditions simultaneously within a single scan.</li><li>A novel attention mechanism, the Medical X-ray Attention (MXA) block, has been introduced to improve X-ray abnormality detection.</li><li>The MXA block integrates local information and broader global context using a specialized module.</li><li>Employing knowledge distillation, the proposed model achieves a substantial improvement over the baseline model, achieving an AUC of 0.85.</li></ul>

Beyond Conventional Transformers: The Medical X-ray Attention (MXA) Block for Improved Multi-Label Diagnosis Using Knowledge Distillation

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