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Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Threats to Federated Learning
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DP-FL: a novel differentially private federated learning framework for the unbalanced data
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inferredcites →https://doi.org/10.1109/bigdata55660.2022.10020232openalex-snapshot
FL-Market: Trading Private Models in Federated Learning
inferredcites →https://doi.org/10.1109/jiot.2020.3037194openalex-snapshot
Local Differential Privacy-Based Federated Learning for Internet of Things
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When Federated Learning Meets Blockchain: A New Distributed Learning Paradigm
inferredcites →https://doi.org/10.1109/tnnls.2022.3216981openalex-snapshot
Privacy and Robustness in Federated Learning: Attacks and Defenses
inferredcites →https://doi.org/10.1109/tpami.2022.3162397openalex-snapshot
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses
inferredcites →https://doi.org/10.1145/3338501.3357370openalex-snapshot
A Hybrid Approach to Privacy-Preserving Federated Learning
inferredcites →https://doi.org/10.1145/3450288openalex-snapshot
A Systematic Literature Review on Federated Machine Learning
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An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning
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Federated Learning and Privacy
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Utility Optimization of Federated Learning with Differential Privacy
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Federated Learning: A Distributed Shared Machine Learning Method
inferredcites →https://doi.org/10.1155/2021/8967819openalex-snapshot
Federated Learning Model with Adaptive Differential Privacy Protection in Medical IoT
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Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
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Advances and Open Problems in Federated Learning
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Towards Understanding the Risks of Gradient Inversion in Federated Learning
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Personalized Treatment through Biosensors and Machine Learning ML
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Federated Learning on Clinical Benchmark Data: Performance Assessment
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A Critical Evaluation of Privacy and Security Threats in Federated Learning
inferredcites →https://doi.org/10.5121/csit.2020.101120openalex-snapshot
Survey on Federated Learning Towards Privacy Preserving AI
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PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation
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Application of Artificial Intelligence-Driven Federated Learning Based on Machine Learning and Deep Learning in Medicine
inferred← citeshttps://doi.org/10.6084/m9.figshare.26733409openalex-snapshot
Additional file 1 of Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility
inferred← citeshttps://doi.org/10.68159/h352855186openalex-snapshot
Federated and Decentralized Machine Learning for Healthcare Systems: A Critical Review of Privacy-Preserving Technologies, Incentive Mechanisms, and Regulatory Compliance Frameworks
inferred← citeshttps://doi.org/10.70675/82876b50z1f73z4b36z973fzeb4b3aba4f6dopenalex-snapshot
Information Extraction from Electronic Health Records : Studies on temporal ordering, privacy and environmental impact
Editorial review for independent work. ICSAC — the Institute for Complexity
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