Applications of machine learning approaches for pediatric asthma exacerbation management: a systematic review.

ABSTRACT:

Background

Pediatric asthma is a common chronic respiratory disease worldwide, and its acute exacerbation events significantly impact children's health and quality of life. Machine learning, an advanced data analysis technique, has shown great potential in healthcare applications in recent years. This systematic review aims to assess the application of ML techniques in pediatric asthma exacerbation and explore their effectiveness and potential value.

Methods

Studies from four electronic databases, including PubMed, EBSCO, Elsevier, and Web of Science, from Jan 2000 to Jan 2025, were searched. Studies applying the ML methods for pediatric asthma exacerbation and published in English were eligible. The risk of bias and applicability of the included studies was assessed using t

SUBMITTER: Zhou C 

PROVIDER: S-EPMC12008861 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature