Dynamic selectout and voting-based federated learning for enhanced medical image analysis

Federated learning (FL) is a promising technique for training machine learning models on distributed, privacy-aware datasets. Nevertheless, FL faces difficulties with agent/client participation, model performance, and the heterogeneous nature of networked data sources when it comes to distributed he...

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Autori principali:	Saeed Iqbal, Adnan N Qureshi, Musaed Alhussein, Khursheed Aurangzeb, Atif Mahmood, Saaidal Razalli Bin Azzuhri
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	IOP Publishing 2025-01-01
Serie:	Machine Learning: Science and Technology
Soggetti:	federated learning dynamic SelectOut mechanisms voting system heterogeneous datasets model performance data privacy
Accesso online:	https://doi.org/10.1088/2632-2153/ada0a6
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