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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Brief Communications
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

Internet

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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