Dermatology Image and Text Dataset for AI-Powered Diagnosis and RAG-Based Medical Support

This dataset has been compiled and derived from publicly available dermatological image collections, including the ISIC 2018 Skin Lesion Dataset and the Atlas Dermatology archive. It comprises 49,100 high-resolution, anonymized images categorized into 32 classes, including 31 dermatological diseases and an additional \u201cUnknown\u201d class to improve real-world generalization. Each image is labeled based on expert classification standards and curated for deep learning applications.In addition to visual data, the dataset integrates a text corpus composed of medical literature related to each disease class. These documents have been segmented into smaller text chunks and transformed into semantic vector representations using OpenAI embeddings. This dual structure enables both image-based disease classification and Retrieval-Augmented Generation (RAG)-based contextual medical support, allowing for reproducible research in multimodal AI-driven diagnostics.This dataset is intended for non-commercial academic use and follows appropriate ethical guidelines. It supports research in medical computer vision, explainable AI, and hybrid decision support systems.