ThalCare Connect

Inspiration

We were inspired by the daily struggles of Thalassemia patients who depend on timely blood transfusions and accessible healthcare. Despite national efforts like e-RaktKosh, the system lacks real-time matching, predictive support, and awareness in rural areas. Our goal was to create a platform that closes these gaps using AI.

What It Does

ThalCare Connect is an AI-powered platform that enables:

• Real-time donor-patient matching
  
• Predictive donor availability
  
• Smart transfusion scheduling
  
• Doctor-patient virtual communication
  
• Multilingual AI chatbot for patient education
  
• Gamified donor dashboard to encourage regular contributions
  

How We Built It

We used:

• React.js and Flutter for the frontend (web + mobile)
• Node.js and Express for the backend
• MongoDB and PostgreSQL for data storage
• Scikit-learn and TensorFlow to build the donor prediction model
• OpenAI API for an educational chatbot
• OAuth2, JWT, AES-256 for secure authentication and encryption
  We also built mock integrations with e-RaktKosh and Blood Bridge.

Challenges We Faced

• Predictive modeling needed clean, anonymized donor datasets
  
• Designing for low-bandwidth users and regional languages
  
• Building a secure but user-friendly system for patient data
  
• Ensuring modularity for future integration with hospital systems
  

What We Learned

• Building AI responsibly for healthcare
  
• The importance of UI simplicity in patient-facing apps
  
• That gamification and community recognition improve donor retention
  
• Legal/ethical considerations in health data handling
  

Built With

• 2.0
• aes-256
• api
• e-raktkosh
• encryption
• express.js
• flutter
• jwt
• mongodb
• node.js
• oauth
• openai
• postgresql
• react.js
• scikit-learn
• tensorflow