Evaluation of Machine Learning Methods Developed for Prediction of Diabetes Complications: A Systematic Review.

ABSTRACT:

Background

With the rising prevalence of diabetes, machine learning (ML) models have been increasingly used for prediction of diabetes and its complications, due to their ability to handle large complex data sets. This study aims to evaluate the quality and performance of ML models developed to predict microvascular and macrovascular diabetes complications in an adult Type 2 diabetes population.

Methods

A systematic review was conducted in MEDLINE®, Embase®, the Cochrane® Library, Web of Science®, and DBLP Computer Science Bibliography databases according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. Studies that developed or validated ML prediction models for microvascular or macrovascular complications in people with Type 2 d

SUBMITTER: Tan KR 

PROVIDER: S-EPMC10012374 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature