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| title: GlycoAI - AI-Powered Glucose Insights | |
| emoji: 🩺 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 4.44.0 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| tags: | |
| - agent-demo-track | |
| - diabetes | |
| - glucose-monitoring | |
| - healthcare-ai | |
| - medical-analysis | |
| - dexcom-api | |
| - mistral-ai | |
| - gradio | |
| - demo | |
| # GlycoAI 🩺 - AI-Powered Glucose Insights | |
| > **Transform your glucose data into actionable health insights with intelligent AI analysis** | |
| [](https://opensource.org/licenses/Apache-2.0) | |
| [](https://gradio.app/) | |
| [](https://huggingface.co/spaces) | |
| [](https://mistral.ai/) | |
| ## 🌟 Overview | |
| GlycoAI is an advanced AI-powered application that analyzes continuous glucose monitoring (CGM) data to provide personalized diabetes management insights. Using state-of-the-art AI agents powered by Mistral AI, GlycoAI transforms complex glucose patterns into clear, actionable recommendations for better diabetes control. | |
| 🎯 Video demo: [deleted ](https://huggingface.co/spaces/Agents-MCP-Hackathon/GlycoAI/blob/main/GlycoAI%20Demo-v1.0.mp4) | |
| ### 🎯 Key Features | |
| - **🤖 Intelligent AI Agent**: Conversational AI that understands glucose patterns and provides personalized insights | |
| - **📊 Comprehensive Analysis**: 14-day glucose trend analysis with clinical metrics (Time in Range, GMI, CV) | |
| - **🎭 Demo Users**: Four realistic patient profiles showcasing different glucose management scenarios | |
| - **🔐 Dexcom Integration**: OAuth-authenticated connection to Dexcom Sandbox API | |
| - **📈 Interactive Visualizations**: Color-coded glucose charts with target range overlays | |
| - **⚠️ Smart Notifications**: Real-time alerts for concerning glucose patterns | |
| - **🏥 Clinical Focus**: Evidence-based recommendations aligned with diabetes care standards | |
| ## 🚀 Live Demo | |
| **Try GlycoAI now:** [https://huggingface.co/spaces/your-username/glycoai](https://huggingface.co/spaces/your-username/glycoai) | |
| ### 🎭 Demo Users Available | |
| 1. **Sarah Thompson** - G7 Mobile - ⚠️ **Unstable Control** (Demonstrates crisis management) | |
| 2. **Marcus Rodriguez** - ONE+ Mobile - Type 2 Diabetes with Dawn Phenomenon | |
| 3. **Jennifer Chen** - G6 Mobile - Athletic lifestyle with excellent control | |
| 4. **Robert Williams** - G6 Receiver - Experienced user with good management | |
| ## 🛠️ Technology Stack | |
| - **Frontend**: Gradio 4.44.0 with custom CSS styling | |
| - **AI Engine**: Mistral AI for intelligent glucose pattern analysis | |
| - **Data Processing**: Pandas, NumPy for glucose data analysis | |
| - **Visualization**: Plotly for interactive glucose charts | |
| - **API Integration**: Dexcom API with OAuth 2.0 authentication | |
| - **Deployment**: Hugging Face Spaces | |
| ## 🏥 Clinical Significance | |
| ### Metrics Analyzed | |
| - **Time in Range (TIR)**: Target >70% (70-180 mg/dL) | |
| - **Time Below Range (TBR)**: Target <4% (<70 mg/dL) | |
| - **Time Above Range (TAR)**: Target <25% (>180 mg/dL) | |
| - **Glucose Management Indicator (GMI)**: Estimated A1C | |
| - **Coefficient of Variation (CV)**: Target <36% (glucose variability) | |
| ### AI Capabilities | |
| - **Pattern Recognition**: Identifies dawn phenomenon, post-meal spikes, nocturnal hypoglycemia | |
| - **Safety Prioritization**: Emphasizes hypoglycemia prevention and severe glucose excursions | |
| - **Personalized Recommendations**: Tailored advice based on individual glucose patterns | |
| - **Clinical Context**: Provides education on diabetes management principles | |
| ## 🔧 Installation & Setup | |
| ### For Local Development | |
| ```bash | |
| # Clone the repository | |
| git clone https://github.com/your-username/glycoai.git | |
| cd glycoai | |
| # Install dependencies | |
| pip install -r requirements.txt | |
| # Set up environment variables | |
| cp .env.example .env | |
| # Edit .env with your API keys: | |
| # MISTRAL_API_KEY=your_mistral_api_key_here | |
| # DEXCOM_CLIENT_ID=your_dexcom_client_id (optional) | |
| # DEXCOM_CLIENT_SECRET=your_dexcom_client_secret (optional) | |
| # Run the application | |
| python app.py | |
| ``` | |
| ### Environment Variables | |
| | Variable | Description | Required | | |
| |----------|-------------|----------| | |
| | `MISTRAL_API_KEY` | Mistral AI API key for chat functionality | ✅ Yes | | |
| | `DEXCOM_CLIENT_ID` | Dexcom developer client ID | ❌ Optional | | |
| | `DEXCOM_CLIENT_SECRET` | Dexcom developer client secret | ❌ Optional | | |
| ## 📖 Usage Guide | |
| ### 1. **Select Data Source** | |
| - Choose from 4 demo users for instant testing | |
| - Or connect via Dexcom Sandbox OAuth (requires developer credentials) | |
| ### 2. **Load Glucose Data** | |
| - Click "Load 14-Day Glucose Data" button | |
| - Watch for notification indicating data quality and patterns | |
| ### 3. **Analyze with AI** | |
| - Navigate to "Chat with AI" tab | |
| - Click on suggested prompts or ask custom questions | |
| - Get personalized insights about glucose patterns | |
| ### 4. **Explore Visualizations** | |
| - View interactive 14-day glucose trends | |
| - Examine detailed statistics and clinical metrics | |
| - Understand time-in-range analysis | |
| ## 🎯 Use Cases | |
| ### For Healthcare Providers | |
| - **Patient Education**: Explain glucose patterns in accessible language | |
| - **Treatment Planning**: Identify areas for intervention | |
| - **Progress Monitoring**: Track improvement over time | |
| - **Clinical Documentation**: Generate insights for medical records | |
| ### For Patients & Caregivers | |
| - **Self-Management**: Understand personal glucose patterns | |
| - **Medication Timing**: Optimize treatment schedules | |
| - **Lifestyle Adjustments**: Learn about food and exercise impacts | |
| - **Safety Awareness**: Recognize dangerous patterns | |
| ### For Researchers & Developers | |
| - **Algorithm Development**: Study glucose pattern recognition | |
| - **AI Applications**: Explore conversational health AI | |
| - **Data Analysis**: Understand CGM data processing | |
| - **Clinical Decision Support**: Build evidence-based tools | |
| ## 🔬 Technical Details | |
| ### Data Processing Pipeline | |
| 1. **Data Ingestion**: Accepts Dexcom API format or generates realistic mock data | |
| 2. **Preprocessing**: Validates timestamps, handles missing values, calculates trends | |
| 3. **Statistical Analysis**: Computes clinical metrics using standardized formulas | |
| 4. **Pattern Recognition**: Identifies glucose variability, meal responses, and anomalies | |
| 5. **AI Context Building**: Structures data for intelligent conversation | |
| ### AI Agent Architecture | |
| - **Context Awareness**: Maintains conversation state with glucose data context | |
| - **Clinical Knowledge**: Trained on diabetes management best practices | |
| - **Safety Focus**: Prioritizes urgent recommendations for dangerous patterns | |
| - **Personalization**: Adapts advice to individual glucose characteristics | |
| ## 📊 Demo Scenarios | |
| ### Sarah Thompson - Crisis Management | |
| - **Scenario**: Highly unstable glucose with frequent dangerous excursions | |
| - **TIR**: ~45% (concerning) | |
| - **CV**: ~52% (very high variability) | |
| - **AI Response**: Urgent safety recommendations and healthcare provider consultation | |
| ### Marcus Rodriguez - Dawn Phenomenon | |
| - **Scenario**: Type 2 diabetes with morning glucose elevation | |
| - **Pattern**: Consistent 6-8 AM glucose rises | |
| - **AI Response**: Medication timing optimization and morning routine adjustments | |
| ### Jennifer Chen - Athletic Lifestyle | |
| - **Scenario**: Active individual with exercise-related glucose variations | |
| - **Pattern**: Exercise-induced lows and recovery patterns | |
| - **AI Response**: Pre/post-workout glucose management strategies | |
| ### Robert Williams - Experienced Management | |
| - **Scenario**: Long-term diabetes with good overall control | |
| - **Focus**: Fine-tuning and maintaining excellent management | |
| - **AI Response**: Advanced optimization strategies and pattern maintenance | |
| ## 🛡️ Privacy & Security | |
| - **Data Processing**: All analysis performed in real-time, no permanent storage | |
| - **API Security**: OAuth 2.0 authentication for Dexcom integration | |
| - **Privacy by Design**: No personal health information retained between sessions | |
| - **Compliance**: Designed with HIPAA principles in mind | |
| - **Transparency**: Open-source approach for algorithm audibility | |
| ## ⚠️ Medical Disclaimer | |
| **IMPORTANT**: GlycoAI is for informational and educational purposes only. This application: | |
| - **IS NOT** a medical device or diagnostic tool | |
| - **DOES NOT** replace professional medical advice | |
| - **SHOULD NOT** be used for treatment decisions without healthcare provider consultation | |
| - **REQUIRES** users to always consult their healthcare team before making management changes | |
| Always follow your healthcare provider's guidance for diabetes management. | |
| ## 🤝 Contributing | |
| We welcome contributions from the healthcare AI, diabetes technology, and open-source communities! | |
| ### Ways to Contribute | |
| - 🐛 **Bug Reports**: Submit issues with detailed reproduction steps | |
| - 💡 **Feature Requests**: Suggest new capabilities or improvements | |
| - 🔧 **Code Contributions**: Submit pull requests with enhancements | |
| - 📚 **Documentation**: Improve guides, examples, and explanations | |
| - 🧪 **Testing**: Help validate algorithms with diverse glucose patterns | |
| ### Development Guidelines | |
| - Follow clinical evidence-based recommendations | |
| - Prioritize patient safety in all features | |
| - Maintain code quality with comprehensive testing | |
| - Document clinical rationale for algorithm decisions | |
| ## 📜 License | |
| This project is licensed under the **Apache License 2.0** - see the [LICENSE](LICENSE) file for details. | |
| ``` | |
| Copyright 2024 GlycoAI Contributors | |
| Licensed under the Apache License, Version 2.0 (the "License"); | |
| you may not use this file except in compliance with the License. | |
| You may obtain a copy of the License at | |
| http://www.apache.org/licenses/LICENSE-2.0 | |
| Unless required by applicable law or agreed to in writing, software | |
| distributed under the License is distributed on an "AS IS" BASIS, | |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| See the License for the specific language governing permissions and | |
| limitations under the License. | |
| ``` | |
| ## 🙏 Acknowledgments | |
| - **Mistral AI** for providing the intelligent conversation capabilities | |
| - **Dexcom** for continuous glucose monitoring technology and API access | |
| - **Diabetes Community** for inspiration and clinical insights | |
| - **Open Source Community** for tools and frameworks that make this possible | |
| - **Healthcare Providers** who guide evidence-based diabetes management | |
| ## 📞 Support & Contact | |
| - **Issues**: [GitHub Issues](https://github.com/your-username/glycoai/issues) | |
| - **Discussions**: [GitHub Discussions](https://github.com/your-username/glycoai/discussions) | |
| - **Documentation**: [Project Wiki](https://github.com/your-username/glycoai/wiki) | |
| - **Email**: your-email@example.com | |
| ## 🚀 Roadmap | |
| ### Upcoming Features | |
| - **Multi-language Support**: Expand accessibility globally | |
| - **Advanced Pattern Recognition**: Machine learning-based anomaly detection | |
| - **Integration Expansion**: Support for additional CGM devices | |
| - **Clinical Decision Support**: Enhanced recommendations for healthcare providers | |
| - **Mobile Optimization**: Improved mobile device experience | |
| - **API Development**: RESTful API for third-party integrations | |
| ### Research Directions | |
| - **Federated Learning**: Privacy-preserving model improvements | |
| - **Predictive Analytics**: Glucose forecasting capabilities | |
| - **Behavioral Analysis**: Lifestyle factor correlation | |
| - **Population Health**: Aggregate insights for public health | |
| --- | |
| **Made with ❤️ for the diabetes community** | |
| *Empowering better glucose management through intelligent AI analysis* |