Artificial intelligence in electrocardiogram signals for sudden cardiac death prediction: a systematic review and meta-analysis.

ABSTRACT:

Purpose

The study aimed to evaluate the diagnostic performance of artificial intelligence (AI) in detecting sudden cardiac death on electrocardiogram (ECG).

Methods

We systematically searched PubMed, Web of Science, Embase, and IEEE Xplore for studies published through April 2025 evaluating AI models for ECG-based sudden cardiac death detection, using expert consensus or database records as the reference standard. A bivariate random-effects model generated pooled sensitivity and specificity estimates. Heterogeneity was quantified via I² and τ² statistics. Study quality was appraised using the revised QUADAS-2 tool, with evidence certainty graded via the GRADE assessment.

Results

Out of 958 initially identified studies, 27 studies with 2613 patien

SUBMITTER: He S 

PROVIDER: S-EPMC12836852 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature