Journal
Kidney360
Publication Date
12-1-2023
Volume
4
Issue
12
First Page
1726
Last Page
1737
Document Type
Open Access Publication
DOI
10.34067/KID.0000000000000299
Rights and Permissions
Lucarelli N, Ginley B, Zee J, Mimar S, Paul AS, Jain S, Han SS, Rodrigues L, Ozrazgat-Baslanti T, Wong ML, Nadkarni G, Clapp WL, Jen KY, Sarder P. Correlating Deep Learning-Based Automated Reference Kidney Histomorphometry with Patient Demographics and Creatinine. Kidney360. 2023 Dec 1;4(12):1726-1737. doi: 10.34067/KID.0000000000000299.© 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Society of Nephrology. This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
Recommended Citation
Lucarelli, Nicholas; Ginley, Brandon; Zee, Jarcy; Mimar, Sayat; Paul, Anindya S.; Jain, Sanjay; Han, Seung Seok; Rodrigues, Luis; Ozrazgat-Baslanti, Tezcan; Wong, Michelle L.; Nadkarni, Girish; Clapp, William L.; Jen, Kuang-Yu; and Sarder, Pinaki, "Correlating deep learning-based automated reference kidney histomorphometry with patient demographics and creatinine." Kidney360. 4, 12. 1726 - 1737. (2023).
https://digitalcommons.wustl.edu/oa_4/4602
Department
ICTS (Institute of Clinical and Translational Sciences)
Additional Links
Supplemental material is available for this article at publisher site.
