Benchmarking federated strategies in Peer-to-Peer Federated learning for biomedical data-Reference-Cited by-同舟云学术

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Benchmarking federated strategies in Peer-to-Peer Federated learning for biomedical data

Published:2023-06 Issue:6 Volume:9 Page:e16925
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Salmeron Jose L.^ORCID,Arévalo Irina^ORCID,Ruiz-Celma Antonio

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference32 articles.

1. Deep learning with differential privacy;Abadi,2016

2. A survey on homomorphic encryption schemes: theory and implementation;Acar;ACM Comput. Surv.,2017

3. Federated deep learning for heterogeneous edge computing;Ahmed,2021

4. Federated learning for healthcare: systematic review and architecture proposal;Antunes;ACM Trans. Intell. Syst. Technol.,2022

5. How to backdoor federated learning;Bagdasaryan,2020

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1. Concurrent vertical and horizontal federated learning with fuzzy cognitive maps;Future Generation Computer Systems;2025-01

2. A cautionary tale on the cost-effectiveness of collaborative AI in real-world medical applications;2024-06-01

3. Federated learning for multi-omics: A performance evaluation in Parkinson’s disease;Patterns;2024-03

4. Privacy-Preserving Breast Cancer Classification: A Federated Transfer Learning Approach;Journal of Imaging Informatics in Medicine;2024-02-29

5. Unleashing the Power of Federated Learning in Fragmented Digital Healthcare Systems: A Visionary Perspective;2023 15th International Conference on Software, Knowledge, Information Management and Applications (SKIMA);2023-12-08

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