Development and validation of a deep learning model to quantify glomerulosclerosis in kidney biopsy specimens

Authors

Jon N. Marsh, Washington University School of Medicine in St. Louis
Ta-Chiang Liu, Washington University School of Medicine in St. Louis
Parker C. Wilson, Washington University School of Medicine in St. Louis
S. Joshua Swamidass, Washington University School of Medicine in St. Louis
Joseph P. Gaut, Washington University School of Medicine in St. Louis

Journal

JAMA Network Open

Publication Date

2021

Volume

4

Issue

1

First Page

e2030939

Document Type

Open Access Publication

DOI

10.1001/jamanetworkopen.2020.30939

Rights and Permissions

Marsh JN, Liu T, Wilson PC, Swamidass SJ, Gaut JP. Development and Validation of a Deep Learning Model to Quantify Glomerulosclerosis in Kidney Biopsy Specimens. JAMA Netw Open. 2021;4(1):e2030939. doi:10.1001/jamanetworkopen.2020.30939. This is an open access article distributed under the terms of the CC-BY License. © 2021 Marsh JN et al. JAMA Network Open.

Recommended Citation

Marsh, Jon N.; Liu, Ta-Chiang; Wilson, Parker C.; Swamidass, S. Joshua; and Gaut, Joseph P., "Development and validation of a deep learning model to quantify glomerulosclerosis in kidney biopsy specimens." JAMA Network Open. 4, 1. e2030939 (2021).
https://digitalcommons.wustl.edu/open_access_pubs/10085