AI RESEARCH
PrivFusion: A Privacy-preserving Multi-Agent Framework for Harmonizing Distributed Datasets
arXiv CS.LG
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ArXi:2605.24249v1 Announce Type: new The growing availability of clinical data has increased the use of machine learning, yet centralized data aggregation is often infeasible for sensitive health information. Federated Learning (FL) offers a distributed alternative, but its adoption is limited by substantial heterogeneity across institutional datasets, making harmonization a critical but frequently overlooked prerequisite for multi-site analytics. We