Exploring the subtle and novel renal pathological changes in diabetic nephropathy using clustering analysis with deep learning

Exploring the subtle and novel renal pathological changes in diabetic nephropathy using clustering analysis with deep learning

Abstract To decrease the number of chronic kidney disease (CKD), early diagnosis of diabetic kidney disease is required. We performed invariant information clustering (IIC)-based clustering on glomerular images obtained from nephrectomized kidneys of patients with and without diabetes. We also used...

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Main Authors: Tomohisa Yabe, Yuko Tsuruyama, Kazutoshi Nomura, Ai Fujii, Yuto Matsuda, Keiichiro Okada, Shogo Yamakoshi, Yuya Hamabe, Shogo Omote, Akihiro Shioya, Norifumi Hayashi, Keiji Fujimoto, Yuki Todo, Tatsuro Tanaka, Sohsuke Yamada, Akira Shimizu, Katsuhito Miyazawa, Hitoshi Yokoyama, Kengo Furuichi
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Diabetic nephropathy
Novel pathological changes
Light microscopy
Deep learning
Invariant information clustering (IIC)
Online Access:https://doi.org/10.1038/s41598-024-84588-6
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https://doi.org/10.1038/s41598-024-84588-6

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