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Federated learning improves site performance in multicenter deep learning without data sharing
OBJECTIVE: To demonstrate enabling multi-institutional training without centralizing or sharing the underlying physical data via federated learning (FL). MATERIALS AND METHODS: Deep learning models were trained at each participating institution using local clinical data, and an additional model was...
Autores principales: | Sarma, Karthik V, Harmon, Stephanie, Sanford, Thomas, Roth, Holger R, Xu, Ziyue, Tetreault, Jesse, Xu, Daguang, Flores, Mona G, Raman, Alex G, Kulkarni, Rushikesh, Wood, Bradford J, Choyke, Peter L, Priester, Alan M, Marks, Leonard S, Raman, Steven S, Enzmann, Dieter, Turkbey, Baris, Speier, William, Arnold, Corey W |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8200268/ https://www.ncbi.nlm.nih.gov/pubmed/33537772 http://dx.doi.org/10.1093/jamia/ocaa341 |
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