A Federated Mining Approach on Predicting Diabetes-Related Complications: Demonstration Using Real-World Clinical Data.
Humayera Islam, Abu Saleh Mohammad Mosa, Famia · PubMed · 2021
of this study is to design a decentralized privacy-protected federated learning architecture that can deliver comparable performance to centralized learning. We demonstrate the potential of adopting federated learning to address the challenges such as class-imbalance in using real-world clinical data. In all our experiments, federated learning showed comparable performance to the gold-standard of centralized learning, and applying class balancing techniques improved performance across all cohorts.