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Facilitating large-scale, cross-institutional collaboration in biomedical machine learning projects requires a trustworthy and resilient federated learning (FL) environment to ensure that sensitive information such as protected health information is kept confidential.
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Kaissis, G. et al · 2021
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Truly privacy-preserving federated analytics for precision medicine with multiparty homomorphic encryption
Froelicher, D. et al · 2021
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Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence
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URL https://www.ibm.com/docs/en/cloud-paks/cp-data/4.5.x?topic=models-federated-learning
Ibm federated learning · 2022
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Tan, A. Z., Yu, H., Cui, L. & Yang, Q · 2022
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AI-powered solutions for healthcare · 2022
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MIDRC CRP10 AI interface - an integrated tool for exploring, testing and visualization of ai models
Gorre, N. et al · 2023
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Improved gradient inversion attacks and defenses in federated learning
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Cloud computing services - Amazon web services · 2023
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Do gradient inversion attacks make federated learning unsafe?
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Predicting “heart age” using electrocardiography
Ball, R. L., Feiveson, A. H., Schlegel, T. T., Starc, V. & Dabney, A. R · 2075
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Federated learning for edge computing: A survey
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