Development and validation of an explainable machine learning model for predicting interstitial fibrosis and tubular atrophy in biopsy-confirmed diabetic nephropathy

BackgroundInterstitial fibrosis and tubular atrophy (IFTA) are key pathological features of chronic kidney damage and progression in diabetic nephropathy (DN). Early identification of patients at higher risk of IFTA may support risk stratification, although reliable non-invasive tools remain limited...

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Detaylı Bibliyografya

Asıl Yazarlar:	Huifang Wang, Longfei Li, Xiaodan Zhang, Demin Xie, Xia Li
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Frontiers Media S.A. 2026-05-01
Seri Bilgileri:	Frontiers in Endocrinology
Konular:	diabetic nephropathy interstitial fibrosis machine learning SHAP tubular atrophy
Online Erişim:	https://www.frontiersin.org/articles/10.3389/fendo.2026.1852512/full
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