Accuracy of Machine Learning in Detecting Pediatric Epileptic Seizures: Systematic Review and Meta-Analysis.

ABSTRACT:

Background

Real-time monitoring of pediatric epileptic seizures poses a significant challenge in clinical practice. In recent years, machine learning (ML) has attracted substantial attention from researchers for diagnosing and treating neurological diseases, leading to its application for detecting pediatric epileptic seizures. However, systematic evidence substantiating its feasibility remains limited.

Objective

This systematic review aimed to consolidate the existing evidence regarding the effectiveness of ML in monitoring pediatric epileptic seizures with an effort to provide an evidence-based foundation for the development and enhancement of intelligent tools in the future.

Methods

We conducted a systematic search of the PubMed, Cochrane, Embase, and Web of Scienc

SUBMITTER: Zou Z 

PROVIDER: S-EPMC11669868 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature