Robust Xception-Based Skin Disease Classification System with Blockchain Integration

Through the application of cutting-edge deep learning techniques, this research aims to transform the prediction of skin illnesses in patients. Xception and Convolutional Neural Network models are integrated with transfer learning to provide a strong prediction framework. Transfer learning uses pre-trained models on patient-specific data to speed up training and increase accuracy. The research takes a fresh tack in addressing data security issues by utilizing block chain technology to safely store patient data while guaranteeing transparency and integrity. The effectiveness of the model is shown on a large scale dataset of images related to skin diseases. Setting new benchmarks in predictive analytics, this combination of transfer learning, sophisticated CNN models, and block chain creates a platform that improves dermatological diagnoses and guarantess a transparent, safe environment for handling patient health data.