E Pluribus Unum (Out of Many, One): Leveraging Federated Learning to Promote Deep Learning Model Development

Safwan S. Halabi

doi:10.1016/j.jacr.2022.06.003

E Pluribus Unum (Out of Many, One): Leveraging Federated Learning to Promote Deep Learning Model Development

Safwan S. Halabi^*

^*Corresponding author for this work

Radiology

Research output: Contribution to journal › Comment/debate › peer-review

1 Scopus citations

Original language	English (US)
Pages (from-to)	967-968
Number of pages	2
Journal	Journal of the American College of Radiology
Volume	19
Issue number	8
DOIs	https://doi.org/10.1016/j.jacr.2022.06.003
State	Published - Aug 2022

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging

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10.1016/j.jacr.2022.06.003

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title = "E Pluribus Unum (Out of Many, One): Leveraging Federated Learning to Promote Deep Learning Model Development",

author = "Halabi, {Safwan S.}",

year = "2022",

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journal = "Journal of the American College of Radiology",

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JO - Journal of the American College of Radiology

JF - Journal of the American College of Radiology

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E Pluribus Unum (Out of Many, One): Leveraging Federated Learning to Promote Deep Learning Model Development

ASJC Scopus subject areas

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