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This is a Quantitative Study study.

September 16, 2025

Out-of-Distribution Performance Analysis of Skin Lesion Classifiers for dermoscopic images

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The VGG model demonstrated the highest performance on the ID test set, achieving an AUROC of 0.895.
Notable performance drops were observed in specific domains with significant distributional shifts in age and diagnosis.
Assessing algorithm robustness under OOD conditions is vital for clinical applications and model trustworthiness.
There is an urgent need for domain-aware evaluation and more diverse data training to ensure clinical relevance.

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This analysis shows OOD performance variability in skin lesion classifiers, suggesting improvements in model training are needed.

Milara et al. (2025) studied this question.

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