Describes a methodology and the resulting dataset of 1,026 dermoscopic images with structured metadata and verified diagnostic labels for medical informatics research.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
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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Methodology for Creating a Clinically Verified Dermoscopic Image Dataset
Describes a methodology and the resulting dataset of 1,026 dermoscopic images with structured metadata and verified diagnostic labels for medical informatics research.
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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.