Author Correction: Federated learning enables big data for rare cancer boundary detection.

Pati, Sarthak; Baid, Ujjwal; Edwards, Brandon; Sheller, Micah; Wang, Shih-Han; Reina, G Anthony; Foley, Patrick; Gruzdev, Alexey; Karkada, Deepthi; Davatzikos, Christos; Sako, Chiharu; Ghodasara, Satyam; Bilello, Michel; Mohan, Suyash; Vollmuth, Philipp; Brugnara, Gianluca; Preetha, Chandrakanth J; Sahm, Felix; Maier-Hein, Klaus; Zenk, Maximilian; ... (2023). Author Correction: Federated learning enables big data for rare cancer boundary detection. Nature communications, 14(1), p. 436. Nature Publishing Group 10.1038/s41467-023-36188-7

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Item Type:

Journal Article (Further Contribution)

Division/Institute:

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04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
04 Faculty of Medicine > Department of Haematology, Oncology, Infectious Diseases, Laboratory Medicine and Hospital Pharmacy (DOLS) > Clinic of Radiation Oncology

UniBE Contributor:

McKinley, Richard Iain, Slotboom, Johannes, Radojewski, Piotr, Meier, Raphael, Wiest, Roland Gerhard Rudi, Reyes, Mauricio

Subjects:

600 Technology > 610 Medicine & health

ISSN:

2041-1723

Publisher:

Nature Publishing Group

Language:

English

Submitter:

Pubmed Import

Date Deposited:

01 Feb 2023 09:09

Last Modified:

02 Mar 2023 23:37

Publisher DOI:

10.1038/s41467-023-36188-7

Related URLs:

PubMed ID:

36702828

BORIS DOI:

10.48350/177975

URI:

https://boris.unibe.ch/id/eprint/177975

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