Predicting diabetic retinopathy based on routine laboratory tests by machine learning algorithms

Predicting diabetic retinopathy based on routine laboratory tests by machine learning algorithms

Abstract Objectives This study aimed to identify risk factors for diabetic retinopathy (DR) and develop machine learning (ML)-based predictive models using routine laboratory data in patients with type 2 diabetes mellitus (T2DM). Methods Clinical data from 4259 T2DM inpatients at Beijing Tongren Hos...

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Bibliographic Details
Main Authors: Xiaohua Wan, Ruihuan Zhang, Yanan Wang, Wei Wei, Biao Song, Lin Zhang, Yanwei Hu
Format: Article
Language:English
Published: BMC 2025-03-01
Series:European Journal of Medical Research
Subjects:
Type 2 diabetes mellitus
Diabetic retinopathy
Routine laboratory tests
Machine learning
XGBoost
Predictive model
Online Access:https://doi.org/10.1186/s40001-025-02442-5
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https://doi.org/10.1186/s40001-025-02442-5

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