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Privacy-preserving federated neural network learning for disease-associated cell classification

Training accurate and robust machine learning models requires a large amount of data that is usually scattered across data silos. Sharing or centralizing the data of different healthcare institutions is, however, unfeasible or prohibitively difficult due to privacy regulations. In this work, we addr...

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Detalles Bibliográficos
Autores principales: Sav, Sinem, Bossuat, Jean-Philippe, Troncoso-Pastoriza, Juan R., Claassen, Manfred, Hubaux, Jean-Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9122966/
https://www.ncbi.nlm.nih.gov/pubmed/35607628
http://dx.doi.org/10.1016/j.patter.2022.100487