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Deep Learning Morphometric Analysis on Protocol Biopsies Predicts Future Graft Function

delete2026-05-06
delete0
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OA
AI
M
Mira Ben Haberou
P
Patrick Bard
J
Jean‐Baptiste Gibier
H
Hugo Gabriel Pereira De Almeida
J
Jamal Bamoulid
M
Mehdi Maanaoui
A
Alice Koenig
M
Maud Rabeyrin
A
Alexia Gazeu
S
Sami Ezzahid
F
Fanny Buron
C
Cécile Picard
C
Cécile Courivaud
S
Sophie Adrian Felix
M
Michel Paindavoine
C
Claire Tinel
R
Rémi Lenain
L
Laurent Martin
G
Georges Tarris
M
Manon Ansart
DOI：10.1016/j.ekir.2026.106585delete
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Abstract

Abstract

En 中文
The predictive value of Banff Classification in protocol transplant biopsies without specific lesions is limited. Morphometry provides precise data on microstructures, surpassing semi-quantitative scores but is time-consuming. This study evaluates whether automated morphometric analysis with deep learning can predict glomerular filtration rate at three years using machine learning.
Keywords:
Kidney biopsy
Deep Learning
Transplantation
Prognosis
Morphometry
Artificial Intelligence
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Kidney International Reports cover
Kidney International Reports
IF:
5.7
Papers:
3.6K
Citations:
7.3K

Organization

No organization information available