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Video.Finale.CareSync.2.mp4
CareSync is an advanced healthcare management system designed to optimize emergency department workflows through artificial intelligence and real-time patient monitoring. This comprehensive platform integrates voice-enabled patient check-in, AI-powered triage analysis, and intelligent workflow management to enhance healthcare delivery efficiency and patient outcomes.
This project was developed as part of the Shipfast w/ Anthropic, Cerebras, Lovable and Windsurf hackathon, demonstrating the integration of cutting-edge AI technologies in healthcare applications.
- Voice-Activated Check-In: Natural language processing powered by Anthropic's Claude AI for seamless patient registration
- Multi-Modal Input: Support for both traditional form-based and voice-driven data collection
- Real-Time Validation: Intelligent form validation with contextual error handling and suggestions
- Medical Image Analysis: AI-powered analysis of injury photographs for preliminary assessment
- Clinical Decision Support: Advanced algorithms for urgency level determination and resource allocation
- Risk Stratification: Automated patient prioritization based on clinical indicators and historical data
- Predictive Analytics: Machine learning models for wait time estimation and treatment duration forecasting
- Multi-Factor Assessment: Integration of vital signs, symptoms, medical history, and visual evidence
- Real-Time Patient Tracking: Live dashboard with drag-and-drop interface for workflow optimization
- Kanban-Style Board: Visual representation of patient progression through emergency department stages
- Automated Status Updates: System-driven patient status transitions with audit trail maintenance
- Resource Optimization: Intelligent allocation of medical staff and equipment based on current demand
- Performance Metrics: Comprehensive dashboard with key performance indicators and trend analysis
- Seasonal Pattern Recognition: Historical data analysis for capacity planning and resource management
- Predictive Modeling: Statistical forecasting for patient volume and resource requirements
- Quality Assurance: Continuous monitoring of care quality metrics and patient satisfaction
- React 18 with TypeScript for type-safe development
- Tailwind CSS for responsive and accessible user interface design
- Shadcn/UI component library for consistent design system implementation
- React Hook Form with Zod validation for robust form management
- Supabase for real-time database operations and authentication
- PostgreSQL with Row Level Security (RLS) for data protection
- Edge Functions for serverless AI processing and external API integration
- Anthropic Claude API for natural language processing and clinical decision support
- Web Speech API for voice recognition and synthesis
- Computer Vision for medical image analysis and assessment
- Role-Based Access Control (RBAC) with medical staff hierarchies
- Comprehensive Audit Logging for all system interactions and data modifications
- Data Encryption for sensitive medical information protection
- HIPAA-Compliant security measures and privacy controls
- Node.js 18.0 or higher
- npm or yarn package manager
- Supabase account and project setup
Create a .env.local file with the following variables:
VITE_SUPABASE_URL=your_supabase_url
VITE_SUPABASE_ANON_KEY=your_supabase_anon_key
ANTHROPIC_API_KEY=your_anthropic_api_key
# Clone the repository
git clone https://github.com/your-username/CareSync-AI-Triage.git
cd CareSync-AI-Triage
# Install dependencies
npm install
# Initialize database schema
npm run db:migrate
# Start development server
npm run dev- Authentication: Log in with assigned medical credentials
- Patient Management: Access patient dashboard for real-time status monitoring
- Triage Assessment: Conduct clinical evaluations with AI-assisted decision support
- Workflow Optimization: Utilize drag-and-drop interface for patient flow management
- Self Check-In: Complete registration using voice or traditional form input
- Medical History: Provide comprehensive health information and current symptoms
- Image Upload: Submit photographs of injuries for AI analysis (optional)
- QR Code Receipt: Receive digital identification for tracking and updates
- Analytics Dashboard: Monitor department performance and resource utilization
- Staff Management: Configure user roles and permissions
- System Configuration: Adjust AI parameters and workflow settings
- Audit Review: Access comprehensive logs for compliance and quality assurance
POST /api/patients- Create new patient recordGET /api/patients- Retrieve patient list with filteringPUT /api/patients/:id- Update patient status and informationPOST /api/triage/analyze- Perform AI-powered triage analysisGET /api/analytics- Generate performance reports and statistics
All API endpoints require authentication via Supabase JWT tokens with appropriate role-based permissions.
The system has been optimized for:
- Sub-second response times for critical operations
- 99.9% uptime through robust error handling and fallback mechanisms
- WCAG 2.1 AA compliance for accessibility standards
- Mobile-responsive design for cross-device compatibility
We welcome contributions from the healthcare technology community. Please review our contribution guidelines and code of conduct before submitting pull requests.
- TypeScript strict mode enabled
- ESLint and Prettier configuration for code consistency
- Comprehensive unit and integration testing
- Security-first development practices
This project is licensed under the MIT License. See the LICENSE file for detailed terms and conditions.
Special thanks to the organizers of the Shipfast hackathon and the supporting technology partners: Anthropic, Cerebras, Lovable, and Windsurf for providing the platform and resources that made this project possible.
For technical inquiries, collaboration opportunities, or deployment assistance, please contact the development team through the project repository or hackathon communication channels.
Disclaimer: This system is designed for educational and demonstration purposes. Any production deployment in healthcare environments must undergo appropriate clinical validation, regulatory approval, and compliance verification.