ThalassoBridge AI

🧠 About the Project: ThalassoBridge AI 🌟 Inspiration Thalassemia continues to be a significant health challenge across India, especially in underserved regions where access to regular blood transfusions, accurate diagnosis, and empathetic support is limited. Inspired by the Blood Warriors Hackathon, our team set out to build a comprehensive AI-powered platform that connects patients, donors, and caregivers in one unified space. Our vision: A single bridge between diagnosis, donor access, and emotional care — with multilingual AI as the heart of it. 🛠️ How We Built It We used Lovable's no-code/low-code interface combined with real code in React, TypeScript, and Tailwind CSS to rapidly prototype and iterate our platform. 🔧 Tech Stack Frontend: React (via Vite) + Tailwind CSS + shadcn-ui Framework: TypeScript-first development UI Components: shadcn-ui + Headless UI AI Integration: OpenAI API for chatbot support Multilingual Support: Prompt chaining & placeholder for Azure Translate Dataset Logic: Blood donation likelihood and thalassemia diagnosis insights based on actual datasets 📦 Project Modules 🎯 Donor Prediction Engine: Uses inputs like Recency, Frequency, Volume, and Time since first donation to calculate donation likelihood using scoring logic derived from the Blood Transfusion Dataset. 🧬 Thalassemia Diagnosis Assistant: Based on the Alpha Thalassemia Dataset, we implemented support logic for interpreting MCV, MCH, HbA2, HbF levels, and other hematological markers. 💬 AI Chatbot with Empathy: A conversational interface preloaded with contextual responses for: Donor eligibility Report interpretation Transfusion timelines Emergency responses Supports English, Hindi, and Tamil, with translation logic extensible to other Indian languages. 🌐 Interactive Frontend UI: Built in Lovable with responsive cards, animated buttons, call-to-action components, and toast alerts. All core buttons now work: Find Blood Donors Get AI Support Register as Donor Schedule Transfusion Emergency Request 🚧 Challenges We Faced Simulating real-time donor matching without backend integration. Designing a UI that’s accessible, emotionally warm, and mobile-friendly. Ensuring culturally sensitive chatbot language across three languages. Making all button actions meaningful even in a front-end prototype. ✅ What We Learned How to integrate AI ethically in healthcare. Dataset translation into meaningful, human-first UX. Multilingual prompt design and intent recognition without LLM over-dependence. Rapid UI prototyping with Lovable’s IDE and Vite environment.

Built With

• alpha
• lovable.dev
• react-(vite)-typescript-tailwind-css-shadcn-ui-openai-api-kaggle-datasets-(blood-transfusion
• thalassemia)