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• W3046929240 abstract "With the increase in Artificial Intelligence driven approaches, researchers are requesting unprecedented volumes of medical imaging data which far exceed the capacity of traditional on-premise client-server approaches for making the data research analysis-ready. We are making available a flexible solution for on-demand de-identification that combines the use of mature software technologies with modern cloud-based distributed computing techniques to enable faster turnaround in medical imaging research. The solution is part of a broader platform that supports a secure high performance clinical data science platform." @default.
• W3046929240 created "2020-08-10" @default.
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• W3046929240 date "2020-08-04" @default.
• W3046929240 modified "2023-09-27" @default.
• W3046929240 title "High performance on-demand de-identification of a petabyte-scale medical imaging data lake." @default.
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