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Kaggle Inc
skin cancer mnist ham10000 ![]() Skin Cancer Mnist Ham10000, supplied by Kaggle Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/skin+disease+dataset+ham10000/ham10000/pmc12881245-387-6-14 Average 86 stars, based on 1 article reviews
skin cancer mnist ham10000 - by Bioz Stars,
2026-10
86/100 stars
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Baidu Inc
synthetic datasets ![]() Synthetic Datasets, supplied by Baidu Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more https://www.bioz.com/product/skin+disease+dataset+ham10000/datasets+synthetic/pmc12938916-279-2-14 Average 86 stars, based on 1 article reviews
synthetic datasets - by Bioz Stars,
2026-10
86/100 stars
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Image Search Results
Journal: Discover Oncology
Article Title: Explainable deep learning for skin cancer detection using swish-activated convolutional networks
doi: 10.1007/s12672-026-04386-6
Figure Lengend Snippet: Illustration of different types of skin cancer lesions included in the HAM10000 dataset, showcasing visual variations between melanoma, basal cell carcinoma, actinic keratosis, vascular lesions and dermatofibroma
Article Snippet: The dataset used in this study,
Techniques:
Journal: Discover Oncology
Article Title: Explainable deep learning for skin cancer detection using swish-activated convolutional networks
doi: 10.1007/s12672-026-04386-6
Figure Lengend Snippet: Class distribution of the HAM10000 dataset before applying data augmentation, showing the imbalance across different skin lesion categories
Article Snippet: The dataset used in this study,
Techniques:
Journal: Discover Oncology
Article Title: Explainable deep learning for skin cancer detection using swish-activated convolutional networks
doi: 10.1007/s12672-026-04386-6
Figure Lengend Snippet: Class distribution of the HAM10000 dataset after applying data augmentation, showing the imbalance across different skin lesion categories
Article Snippet: The dataset used in this study,
Techniques: