Predicting paediatric asthma exacerbations with machine learning: a systematic review with meta-analysis.

ABSTRACT:

Background

Asthma exacerbations in children pose a significant burden on healthcare systems and families. While traditional risk assessment tools exist, artificial intelligence (AI) offers the potential for enhanced prediction models.

Objective

This study aims to systematically evaluate and quantify the performance of machine learning (ML) algorithms in predicting the risk of hospitalisation and emergency department (ED) admission for acute asthma exacerbations in children.

Methods

We performed a systematic review with meta-analysis, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The risk of bias and applicability for eligible studies was assessed according to the prediction model study risk of bias assessment too

SUBMITTER: Votto M 

PROVIDER: S-EPMC11558535 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature