Describes a methodology and the resulting dataset of 1,026 dermoscopic images with structured metadata and verified diagnostic labels for medical informatics research.
PAD-UFES-20: A skin lesion dataset composed of patient data and clinical images collected from smartphones // Data in Brief.\,---\,2020.\,---\,Vol.\,32.\,---\,Article 106221
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Benchmark of twelve models finds hybrid CNN-transformer architectures and a SigLIP vision-language model deliver the strongest overall performance on skin cancer detection using the PAD-UFES-20 dataset.
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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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CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection
Benchmark of twelve models finds hybrid CNN-transformer architectures and a SigLIP vision-language model deliver the strongest overall performance on skin cancer detection using the PAD-UFES-20 dataset.