Development and Validation of a Deep Learning Model to Quantify Glomerulosclerosis in Kidney Biopsy...
Development and Validation of a Deep Learning Model to Quantify Glomerulosclerosis in Kidney Biopsy Specimens
About this item
Full title
Author / Creator
Publisher
United States: American Medical Association
Journal title
Language
English
Formats
Publication information
Publisher
United States: American Medical Association
Subjects
More information
Scope and Contents
Contents
A chronic shortage of donor kidneys is compounded by a high discard rate, and this rate is directly associated with biopsy specimen evaluation, which shows poor reproducibility among pathologists. A deep learning algorithm for measuring percent global glomerulosclerosis (an important predictor of outcome) on images of kidney biopsy specimens could...
Alternative Titles
Full title
Development and Validation of a Deep Learning Model to Quantify Glomerulosclerosis in Kidney Biopsy Specimens
Authors, Artists and Contributors
Author / Creator
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7818108
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7818108
Other Identifiers
ISSN
2574-3805
E-ISSN
2574-3805
DOI
10.1001/jamanetworkopen.2020.30939
