Thalassemia management system

An AI-powered Thalassemia Management & Donor-Connect System predicting transfusion needs, sending reminders, managing donors, and uniting hospitals with real-time urgency and performance tracking

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***Inspiration***

Thalassemia patients require lifelong blood transfusions, and delays in scheduling or poor donor coordination often risk their health. Seeing this challenge firsthand inspired us to create an AI-powered Thalassemia Management and Donor-Connect System that provides timely, predictive, and efficient support for patients, donors, and hospitals.

***What We Learned***

How machine learning models can predict medical needs like the next transfusion date and required blood units using features such as Hb, iron, and transfusion history.

The importance of secure data handling (e.g., Aadhar verification) and age-based updates.

How to design real-time dashboards and global urgency tables for hospital coordination.

Collaboration between patients, donors, and hospitals through notifications and leaderboards.

****** How We Built It******

Data: We created a structured patient dataset with fields like Hb, Iron, Weight, Last Transfusion Days, and Blood Group.

AI Model: Trained using regression and time-series approaches (e.g., XGBoost, SVM).

Backend: Implemented admin routes for registration, appointments, donor matching, and notifications.

Frontend: Designed hospital dashboards with filters (city, state, urgency).

Leaderboard: A gamified ranking system tracking hospital performance across India.

******* Challenges We Faced******

Creating a realistic patient dataset while ensuring privacy.

Handling real-time updates (age updates, Aadhar after 11 years).

Ensuring accuracy in transfusion predictions despite limited records.

Designing a scalable urgency filter system for hospitals across multiple locations.

Building smooth donor-patient matching while avoiding duplication.

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