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Development and Validation of a Machine Learning Model for Differentiating Diabetic Kidney Disease and Non-Diabetic Kidney Disease in Type 2 Diabetes
Sponsor: Beijing Tongren Hospital
Summary
This multicenter retrospective observational study aims to develop and validate an interpretable machine learning model for differentiating diabetic kidney disease (DKD) from non-diabetic kidney disease (NDKD) in patients with type 2 diabetes mellitus. Clinical, laboratory, and pathological data from biopsy-confirmed patients were collected from 14 medical centers in China. Multiple machine learning algorithms were evaluated and externally validated. The final model was implemented as a web-based clinical decision support tool.
Official title: Development and Validation of an Interpretable Machine Learning Model for Noninvasive Differentiation of Diabetic Kidney Disease and Non-Diabetic Kidney Disease in Type 2 Diabetes: A Multicenter Retrospective Cohort Study
Key Details
Gender
All
Age Range
18 Years - 70 Years
Study Type
OBSERVATIONAL
Enrollment
2201
Start Date
2019-01-01
Completion Date
2024-12-01
Last Updated
2026-06-29
Healthy Volunteers
Not specified
Locations (1)
Beijing Tongren Hospital
Beijing, Beijing Municipality, China