Article

A Heterogeneity-Aware Privacy-Preserving Federated Learning Framework Using Ensemble Clustering for Healthcare Applications

2026-04-22

Abstract excerpt

<title>Abstract</title> <p>Data heterogeneity remains one of the most significant challenges in federated learning (FL), impacting model performance, convergence, and scalability. This issue is especially critical in healthcare, where data is distributed across multiple institutions, devices, and geographical regions, and privacy preservation is paramount. In this study, we propose a novel hybrid algorithm, Dynam...

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Literature Corpus work: 412d4e86-271a-54fc-acdf-26e60aef64a8
DOI: 10.21203/rs.3.rs-8191856/v1

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