Exploring Machine Learning Applications in Pediatric Asthma Management: Scoping Review.

ABSTRACT:

Background

The integration of machine learning (ML) in predicting asthma-related outcomes in children presents a novel approach in pediatric health care.

Objective

This scoping review aims to analyze studies published since 2019, focusing on ML algorithms, their applications, and predictive performances.

Methods

We searched Ovid MEDLINE ALL and Embase on Ovid, the Cochrane Library (Wiley), CINAHL (EBSCO), and Web of Science (core collection). The search covered the period from January 1, 2019, to July 18, 2023. Studies applying ML models in predicting asthma-related outcomes in children aged <18 years were included. Covidence was used for citation management, and the risk of bias was assessed using the Prediction Model Risk of Bias Assessment Tool.

Results

From

SUBMITTER: Ojha T 

PROVIDER: S-EPMC11387921 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature