An Integrated Platform for Thalassemia Risk Prediction and Donor Assistance using Machine Learning

  • Unique Paper ID: 196725
  • Volume: 12
  • Issue: 11
  • PageNo: 3887-3894
  • Abstract:
  • This project introduces a Thalassemia Risk Prediction and Donor Management System that combines a React-based interface with a machine learning model for early detection and care. Patients can input clinical data, register, check donor availability, and schedule consultations, while the model classifies users as Normal, Carrier, or Patient in real time. The system also predicts donor eligibility, processes donation requests, and matches patients with suitable donors, bridging the gap between diagnosis and care. It supports cloud deployment, integration with hospital systems, and tools like WhatsApp bots for scalability and accessibility. By enabling early intervention, counseling, and donor-recipient matching, the solution promotes awareness and collaboration among patients, caregivers, and clinicians.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{196725,
        author = {P. VENKATESWAR REDDY and K. SUBHASH and G. RAMA MOHAN REDDY and K. REVANTH KUMAR REDDY and G. NARESH KUMAR REDDY and P. HARI KRISHNA},
        title = {An Integrated Platform for Thalassemia Risk Prediction and Donor Assistance using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {3887-3894},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=196725},
        abstract = {This project introduces a Thalassemia Risk Prediction and Donor Management System that combines a React-based interface with a machine learning model for early detection and care. Patients can input clinical data, register, check donor availability, and schedule consultations, while the model classifies users as Normal, Carrier, or Patient in real time. The system also predicts donor eligibility, processes donation requests, and matches patients with suitable donors, bridging the gap between diagnosis and care. It supports cloud deployment, integration with hospital systems, and tools like WhatsApp bots for scalability and accessibility. By enabling early intervention, counseling, and donor-recipient matching, the solution promotes awareness and collaboration among patients, caregivers, and clinicians.},
        keywords = {Thalassemia Risk Prediction, ML, Donor Manager, React-based UI, Healthcare Screener, Blood Donation, Predictive Modeling, Cloud Deployment, WhatsApp Bot, Clinical Data Analysis, Patient Support System, Real-time Diagnosis, Medical Data Processing, Health Informatics.},
        month = {April},
        }

Cite This Article

REDDY, P. V., & SUBHASH, K., & REDDY, G. R. M., & REDDY, K. R. K., & REDDY, G. N. K., & KRISHNA, P. H. (2026). An Integrated Platform for Thalassemia Risk Prediction and Donor Assistance using Machine Learning. International Journal of Innovative Research in Technology (IJIRT), 12(11), 3887–3894.

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