Skin Disease Identification and Skincare Solutions Using Deep Learning Approach

The major challenge in dermatology is the accurate diagnosis and treatment of skin disorders. This issue can be addressed by using advanced machine-learning techniques. In this paper, we propose a hybrid deep-learning architecture consisting of Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) for predicting skin diseases more accurately in an automated way. By analyzing the input image of the diseased skin, the AI-based prediction system offers timely medical interventions and supports doctors in making well-informed treatment decisions. Achieving a prediction accuracy of 95.09 %, the proposed ensemble model is capable of detecting various skin diseases and also is designed to provide personalized skincare recommendations. Further, we have designed a user-friendly application that integrates seamlessly into existing healthcare systems and ensures data privacy and security in compliance with strict regulations. The proposed diagnostic platform aims to revolutionize dermatological care, making diagnosis and treatment more efficient and leading to improved patient outcomes.