AI Healthcare Assistant

Live Project
AI Healthcare Assistant
2024
FlutterDartGolangPythonFastAPIPostgreSQL+2
Overview
An innovative AI-powered healthcare application developed for Yotto Health, focused on diabetes management through intelligent monitoring and personalized recommendations. The app leverages Large Language Models to provide actionable health insights and improve patient outcomes.
Key Features:
Technical Highlights:
Key Features:
- 🤖 AI-Powered Insights: LLM integration for personalized health recommendations
- 📊 Glucose Monitoring: Real-time tracking and analysis of blood glucose levels
- 💊 Medication Reminders: Intelligent medication scheduling and adherence tracking
- 📈 Trend Analysis: Machine learning models to identify health patterns
- 🔔 Smart Alerts: Proactive notifications for abnormal readings and missed medications
- 👨⚕️ Doctor Dashboard: Healthcare provider portal for patient monitoring
- 📱 Cross-Platform: Native Flutter apps for iOS and Android devices
Technical Highlights:
- Integrated Pi 4 LLM for on-device AI processing ensuring patient data privacy
- Built high-performance backend using Golang for real-time data processing
- Developed Flutter mobile applications with smooth animations and intuitive UI
- Implemented PostgreSQL for secure health data storage with HIPAA compliance considerations
- Created FastAPI Python services for ML model inference and data analysis
- Designed offline-first architecture for critical health monitoring features
My Role
Software Engineer
Key contributor to AI healthcare platform development:
Key contributor to AI healthcare platform development:
- 🤖 AI Integration: Implemented Pi 4 LLM integration for intelligent health insights
- 📱 Mobile Development: Built Flutter apps for iOS and Android with healthcare-focused UX
- 🐍 Backend Services: Developed FastAPI Python services for ML model deployment
- 🗄️ Data Architecture: Designed secure database schema for health data storage
- ⚡ Performance: Optimized app performance for real-time health monitoring
- 🔐 Privacy: Implemented privacy-first approach with local AI processing when possible