Privacy-Preserving, Robust, and Explainable Federated Learning Framework for Healthcare System
Principal Investigators & Key Members:
Bo Li
| Kok-Seng Wong
| Dam Thuy Trang
| Luu Hong Nhung
| Khoa Doan
The project focuses on designing a trustworthy federated learning (FL) framework for the healthcare system with theoretical guarantees for its privacy, robustness, and agent-level data valuation and explainability, aiming to make the healthcare systems more efficient and trustworthy.