A machine learning model for predicting the risk of diabetic nephropathy in individuals with type 2 diabetes mellitus.

ABSTRACT:

Introduction

Diabetic kidney disease (DKD) represents the predominant form of chronic kidney disease (CKD) linked with diabetes mellitus. The application of artificial intelligence holds promise for delaying renal deterioration and decreasing treatment expenses by facilitating early detection and intervention. This is contingent upon the development of an efficient and user-friendly model for predicting DKD risk in diabetic individuals. In this study, leveraging extensive clinical datasets, we sought to develop and validate a predictive model employing machine learning techniques to assess the risk of DKD in patients with type 2 diabetes mellitus (T2DM).

Research design and methods

We conducted a retrospective collection of clinical data from 10,057 patients diagnosed with T

SUBMITTER: Li T 

PROVIDER: S-EPMC12568428 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature