Cascade classification improves macro F1 over single-stage for some models by allowing sensitivity control but reveals a large generalization gap on external clinical data.
Deep learn- ing outperformed 136 of 157 dermatologists in a head-to-head dermo- scopic melanoma image classification task.European Journal of Cancer
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Prospective single-center validation of a cascade deep learning dermoscopy CDSS found no false negatives for five malignant lesions and 88.3% specificity, with quantitative IoU assessment of attention maps.
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Cascade Classification of Dermoscopic Images of Skin Neoplasms with Controllable Sensitivity and External Clinical Validation
Cascade classification improves macro F1 over single-stage for some models by allowing sensitivity control but reveals a large generalization gap on external clinical data.
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Clinical Validation of the Melanoscope AI Mobile Dermoscopy Clinical Decision Support System
Prospective single-center validation of a cascade deep learning dermoscopy CDSS found no false negatives for five malignant lesions and 88.3% specificity, with quantitative IoU assessment of attention maps.