Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data

Understand

In clinical research, the lack of events of interest often necessitates imbalanced learning.

• One approach to resolve this obstacle is data integration or sharing, but due to privacy concerns neither is practical.
• Therefore, there is an increasing demand for a platform on which an analysis can be performed in a federated environment while maintaining privacy.
• However, it is quite challenging to develop a federated learning algorithm that can address both privacy-preserving and class imbalanced issues.