ISIC-DICM-17K

ISIC-DICM-17K (ISIC Dermoscopic Images and Clinical Metadata 17K) is a curated and balanced dataset derived from the International Skin Imaging Collaboration (ISIC) Archive Gallery. It comprises 17,060 dermoscopic images and clinical metadata (8,530 melanoma and 8,530 non-melanoma classes). For more details, please follow the project’s GitHub repository: [https://github.com/mmu-dermatology-research/isic-dicm-17k](https://github.com/mmu-dermatology-research/isic-dicm-17k) This dataset was used in this study and benchmark to explore the effectiveness of multimodal learning for skin lesion classification: S. Ahammed, X. Cui, W. Lu and M. H. Yap, "Skin Lesion Classification using Dermoscopic Images and Clinical Metadata: Insights from Multimodal Models," 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Nashville, TN, USA, 2025, pp. 222-230, DOI: 10.1109/CVPRW67362.2025.00027