A Multi-Modal AI Approach for Dermatological Diagnosis

Skin is essential for maintaining it in good condition; identifying skin conditions through lesion images is insufficient; we require both visual and medical information. Although artificial intelligence has improved in recent days at predicting skin conditions from lesion images, most of the current systems are absent of medical content and instead focus on visual analysis. This research addresses the gap by building a diagnostic support framework that incorporates lesion image analysis with relevant medical knowledge. At the core of the system is a vision transformer (ViT), which analyses lesion images to predict possible skin diseases. From there, the system retrieves relevant medical information using RAG to support a more reliable diagnosis. It then goes a step further, generating clear diagnostic explanations, treatment suggestions and general healthcare guidance that the user can actually act on. The system is designed to be both trustworthy and practical-genuinely useful for real diagnostic decision-making