This paper proposes Dynamic Trust-Aware Federated Aggregation (DTAFA), which evaluates each participating site through gradient quality, behavioral consistency, and data integrity, then smooths the resulting trust score across rounds, and combines cohort size, smoothed trust, and a current-round quality gate.
: The increasing adoption of virtual hospitals and Internet of Medical Things (IoMT)-driven clinical workflows demands service composition mechanisms that can operate reliably under strict privacy constraints and heterogeneous provider ecosystems. Traditional trust-based composition approaches, such as majority voting...
Hédi Hamdi, Zaki Brahmi, Sabeur Lajili et al.· Computer Modeling in Enginee...· 0 citations
Federated Learning (FL) holds promise for digital health by enabling collaborative model training without compromising patient data privacy. However, differences in data completeness, censoring rates, patient populations, institutional reliability, and contribution quality across healthcare institutions remain major ch...
Navid Seidi, Satyaki Roy, Sajal K. Das· IEEE journal of biomedical a...· 0 citations
The results demonstrate that strong privacy protection, communication efficiency, and high diagnostic reliability can coexist within large-scale federated healthcare systems, making FedDeepRiskNet + + a practical solution for next-generation medical IoT systems.
Ibrahim Aqeel, Emad S. Hassan, Noha Mostafa et al.· Cluster Computing· 0 citations
A federated learning framework with data locality for healthcare diagnostics that enables multiple hospitals to jointly train accurate models while keeping patient data within institutional boundaries is introduced.
Rakeshkumarreddy Ambati· International Journal of Art...· 0 citations
With Federated Learning (FL), hospitals are able to train models together without moving patient data, which is important due to security laws such as HIPAA and GDPR that make most deployments legally prohibit training models with patient data in a central location. The larger issue is statistical. Hospitals likely hav...
Zubair Raja Ahamed Zaffarullah, Venkata M. Gudala, J. M. Shanthi et al.· 2026 International Conferenc...· 0 citations
The proposed FSSL framework provides a scalable foundation for privacy-conscious collaborative clinical AI while keeping patient data within the originating healthcare institution and is intended to support, rather than replace, professional clinical decision-making.
A. V, S. Swathi, G. Sharmila et al.· International journal of com...· 0 citations
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