Interpretable Machine Learning Model for Predicting and Assessing the Risk of Diabetic Nephropathy: Prediction Model Study.

ABSTRACT:

Background

Diabetic nephropathy (DN), a severe complication of diabetes, is characterized by proteinuria, hypertension, and progressive renal function decline, potentially leading to end-stage renal disease. The International Diabetes Federation projects that by 2045, 783 million people will have diabetes, with 30%-40% of them developing DN. Current diagnostic approaches lack sufficient sensitivity and specificity for early detection and diagnosis, underscoring the need for an accurate, interpretable predictive model to enable timely intervention, reduce cardiovascular risks, and optimize health care costs.

Objective

This study aimed to develop and validate a machine learning-based predictive model for DN in patients with type 2 diabetes, with a focus on achieving high predi

SUBMITTER: Wen Y 

PROVIDER: S-EPMC12543291 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature