📌 System Overview

This platform presents a deep learning–based AI-assisted skin disease diagnosis system, supporting the upload and real-time prediction of both dermoscopic and clinical images. In addition, it provides an overview of the research workflow, a detailed introduction to the proposed DCSNeXt model, and dataset descriptions. The system is designed for researchers, clinicians, and students, with the goal of fostering the integration and synergy between artificial intelligence and medical expertise.

🖼️ How to Use

• Upload Images: Use the “Dermoscopic Prediction” and “Clinical Prediction” buttons to access the respective pages and upload dermoscopic or clinical images.
• Predict: Select the target skin lesion image to initiate model inference.
• View Results: The predicted category and confidence score will be displayed below. Future updates will include features such as explainability heatmaps, lesion information, and preliminary treatment recommendations.
• Test Samples: You may also try the built-in sample images for demonstration and testing.

⚠️ Notes

🔹 The prediction results provided by this system are intended solely for research, education, and as auxiliary support for physicians. They must not be used as the sole basis for medical diagnosis or treatment decisions.
🔹 Model performance may vary due to factors such as imaging conditions, data quality, image resolution, and lesion type.
🔹 For clinical application, predictions must always be combined with clinical examinations, laboratory testing, and expert interpretation to ensure diagnostic accuracy and patient safety.

📖 Additional Support

🔹 For further technical support or collaboration inquiries, please contact the research group of Professor Zuquan Weng at Fuzhou University, Fuzhou, Fujian, China.
🔹 Relevant publications and the corresponding author’s contact information are available on the main page of this system.