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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2022
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| 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 |