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"Federated Learning Enables Big Data for Rare Cancer Boundary Detection."

Sarthak Pati et al. (2022)

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DOI: 10.48550/ARXIV.2204.10836

access: open

type: Informal or Other Publication

metadata version: 2022-04-25

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  dblp key:
  - journals/corr/abs-2204-10836
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  persistent URL:
  - https://dblp.org/rec/journals/corr/abs-2204-10836
Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah J. Sheller, Hans Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus H. Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey D. Rudie, Javier E. Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña Quintero, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S. Alexander, et al.:
Federated Learning Enables Big Data for Rare Cancer Boundary Detection. CoRR abs/2204.10836 (2022)

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