2026-10-12T07:50:28Z https://data.mendeley.com/oai

oai:data.mendeley.com/yj3md44hxg.2 2025-06-26T08:57:26Z

Sultana, Marjia SkinDisNet: A Multi-Class Clinical Images and Metadata for Skin Disease Mendeley Data Purpose : Classification and identification of six different skin disease categories for automatic diagnosis. Type of data: Image files (512 x 512 pixels) Data format: Joint Photographic Expert Group (JPG) and Comma Separated Values (CSV) file formats Number of classes: Six (Atopic Dermatitis, Contact Dermatitis, Eczema, Scabies, Seborrheic Dermatitis, and Tinea Corporis) Number of images: Preprocessed Folder: 1710 images Augmented Folder: 11970 images Metadata: The metadata associated with each skin lesion is composed of 7 attributes. All attributes are available in a CSV document. In total, there are 416 patients and 1,710 skin disease images present in the dataset. Each image/sample has a reference to the patient and the skin disease in the metadata. Data Acquisition: Images were captured using smartphone cameras during the patients’ consultations with dermatologists. Data source: Clinical sources: 1. Institution: Rangpur Medical College, City: Rangpur, Country: Bangladesh 2. Institution: Shahid Syed Nazrul Islam Medical College, City: Kishoreganj, Country: Bangladesh Applications: Skin disease detection and classification, diagnosis systems, medical image analysis, computer vision and more. Computer Vision Dermatology Machine Learning Image Classification Medical Image Processing Sajib, Rakib Hossain Badhan, Iffat Ara Ahmed, Mizu Bushra, Moumita Yasmin Dataset doi:10.17632/yj3md44hxg.2 oai:data.mendeley.com/yj3md44hxg.2 Attribution Noncommercial 4.0 International https://creativecommons.org/licenses/by-nc/4.0/ https://data.mendeley.com/datasets/yj3md44hxg 2025-06-26T08:57:26Z