End-to-end interstitial fibrosis assessment of kidney biopsies with a machine learning-based model
Journal
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Journal Volume
37
Journal Issue
11
Pages
2093
Date Issued
2022-10-19
Author(s)
Liu, Zhi-Yong
Lin, Chi-Hung
Wang, Hsiang-Sheng
Wen, Mei-Chin
Huang, Shun-Chen
Tu, Kun-Hua
Kuo, Chang-Fu
Chen, Tai-Di
Abstract
The extent of interstitial fibrosis in the kidney not only correlates with renal function at the time of biopsy but also predicts future renal outcome. However, its assessment by pathologists lacks good agreement. The aim of this study is to construct a machine learning-based model that enables automatic and reliable assessment of interstitial fibrosis in human kidney biopsies.
Subjects
interstitial fibrosis; machine learning; reliability; reproducibility; whole-slide imaging
SDGs
Publisher
OXFORD UNIV PRESS
Type
journal article