🚀 Live Demo
Experience our AI-powered diabetic retinopathy detection system in action. Upload OCT images and get instant analysis with Grad-CAM visualizations.
Launch Live DemoAI-Powered Analysis
State-of-the-art ResNet-50 model trained on extensive OCT image datasets for accurate diabetic retinopathy detection.
Grad-CAM Visualization
Advanced explainable AI technology that highlights the specific areas of OCT images that influence the AI's diagnosis.
Confidence Scoring
Get detailed confidence scores and probability assessments for each diagnosis, ensuring reliable results.
Result Storage
Automatically save analyzed images with timestamps, predictions, and confidence scores for future reference.
Batch Processing
Process multiple OCT images simultaneously with comprehensive CSV reporting and batch analysis capabilities.
Web Interface
User-friendly Gradio web interface accessible from any device with a modern web browser.
⚠️ Medical Disclaimer
This tool is for research and educational purposes only. It should not be used for actual medical diagnosis without proper validation and clinical oversight. Always consult with qualified healthcare professionals for medical diagnosis and treatment decisions.
📚 Open Source Project
This project is completely open source and available on GitHub. Contribute, fork, or star the repository to support the development of AI-powered medical imaging tools.
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