Supervised Learning–Based Clinical Decision Support System for Disease Prediction

Skin diseases are among the most common health disorders affecting people worldwide. Early detection and accurate diagnosis are essential to prevent complications and long-term health issues. However, access to dermatological expertise is limited in many rural and underdeveloped regions. This research presents a Skin Disease Prediction System based on Deep Learning and Image Processing techniques. The system uses a Convolutional Neural Network model trained on labeled dermatological image datasets to classify various skin diseases. The trained model is integrated into a web-based application that allows users to upload images for real-time prediction. The experimental results demonstrate high accuracy and reliability, making the system suitable as a supportive diagnostic tool in telemedicine and remote healthcare environments.