Machine Learning-Based Prediction of Neurodegenerative Disease in Patients With Type 2 Diabetes by Derivation and Validation in 2 Independent Korean Cohorts: Model Development and Validation Study.

ABSTRACT:

Background

Several machine learning (ML) prediction models for neurodegenerative diseases (NDs) in type 2 diabetes mellitus (T2DM) have recently been developed. However, the predictive power of these models is limited by the lack of multiple risk factors.

Objective

This study aimed to assess the validity and use of an ML model for predicting the 3-year incidence of ND in patients with T2DM.

Methods

We used data from 2 independent cohorts-the discovery cohort (1 hospital; n=22,311) and the validation cohort (2 hospitals; n=2915)-to predict ND. The outcome of interest was the presence or absence of ND at 3 years. We selected different ML-based models with hyperparameter tuning in the discovery cohort and conducted an area under the receiver operating characteristic curv

SUBMITTER: Sang H 

PROVIDER: S-EPMC11487204 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature