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Georgia State University
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Expert allocation in retinal pathology detection is not only disease-dependent but also enhances interpretability, revealing how models can effectively disentangle complex co-occurring conditions.
C$^2$A boosts multi-label chest X-ray classification accuracy by effectively leveraging spatial evidence and clinical co-occurrence, achieving a remarkable AUROC of 0.895.
