Journal
Nature Communications
Publication Date
12-5-2022
Volume
13
Issue
1
First Page
7346
Document Type
Open Access Publication
DOI
10.1038/s41467-022-33407-5
Rights and Permissions
Pati, S., Baid, U., Edwards, B. et al. Federated learning enables big data for rare cancer boundary detection. Nat Commun 13, 7346 (2022). https://doi.org/10.1038/s41467-022-33407-5 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Recommended Citation
Pati, Sarthak; LaMontagne, Pamela; Marcus, Daniel; and et al., "Federated learning enables big data for rare cancer boundary detection." Nature Communications. 13, 1. 7346 (2022).
https://digitalcommons.wustl.edu/oa_4/1034
Additional Links
Supplemental material is available for this article at publisher site.
