Development and Validation of a Deep Learning Model to Quantify Glomerulosclerosis in Kidney Biopsy Specimens-Reference-Cited by-同舟云学术

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Development and Validation of a Deep Learning Model to Quantify Glomerulosclerosis in Kidney Biopsy Specimens

Published:2021-01-20 Issue:1 Volume:4 Page:e2030939
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Marsh Jon N.¹²,Liu Ta-Chiang¹,Wilson Parker C.¹,Swamidass S. Joshua¹²,Gaut Joseph P.¹³

Affiliation:

1. Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, Missouri

2. Institute for Informatics (I2), Washington University School of Medicine in St Louis, St Louis, Missouri

3. Department of Medicine, Washington University School of Medicine in St Louis, St Louis, Missouri

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2775298/marsh_2021_oi_200971_1610397622.63212.pdf

Reference35 articles.

1. Improving the supply and quality of deceased-donor organs for transplantation.;Tullius;N Engl J Med,2018

2. OPTN/SRTR 2017 annual data report: kidney.;Hart;Am J Transplant,2019

3. Evaluation of donor kidneys prior to transplantation: an update of current and emerging methods.;Moeckli;Transpl Int,2019

4. Early experience with the new kidney allocation system: a perspective from UNOS.;Stewart;Clin J Am Soc Nephrol,2017

5. Preoperative assessment of the deceased-donor kidney: from macroscopic appearance to molecular biomarkers.;Dare;Transplantation,2014

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