PrivFusion: A Privacy-preserving Multi-Agent Framework for Harmonizing Distributed Datasets

In three linesPrivFusion is a privacy-preserving multi-agent framework that automates harmonization of heterogeneous datasets before federated training. Tested on four COVID-19 datasets, it uses agents to analyze local data, cluster semantically similar features, and recommend iterative transformations without centralizing sensitive health information.

Summary generated by Claude — human-verified