Secure federated learning applied to medical imaging with fully homomorphic encryption

Research article (2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC), 2024) · cited 19× · AI/ML
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Secure federated learning applied to medical imaging with fully homomorphic encryption

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Secure federated learning applied to medical imaging with fully homomorphic encryption is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Secure federated learning applied to medical imaging with fully homomorphic encryption. Retrieved May 24, 2026, from https://4ort.xyz/entity/secure-federated-learning-applied-to-medical-imaging-with-fully-homomorphic-encryption
MLA “Secure federated learning applied to medical imaging with fully homomorphic encryption.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/secure-federated-learning-applied-to-medical-imaging-with-fully-homomorphic-encryption.
BibTeX @misc{4ortxyz_secure-federated-learning-applied-to-medical-imaging-with-fully-homomorphic-encryption_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Secure federated learning applied to medical imaging with fully homomorphic encryption}}, year = {2026}, url = {https://4ort.xyz/entity/secure-federated-learning-applied-to-medical-imaging-with-fully-homomorphic-encryption}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Secure federated learning applied to medical imaging with fully homomorphic encryption — https://4ort.xyz/entity/secure-federated-learning-applied-to-medical-imaging-with-fully-homomorphic-encryption (retrieved 2026-05-24)

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