Sudden cardiac arrest prediction via deep learning electrocardiogram analysis.

ABSTRACT:

Aims

Sudden cardiac arrest (SCA) is a commonly fatal event that often occurs without prior indications. To improve outcomes and enable preventative strategies, the electrocardiogram (ECG) in conjunction with deep learning was explored as a potential screening tool.

Methods and results

A publicly available data set containing 10 s of 12-lead ECGs from individuals who did and did not have an SCA, information about time from ECG to arrest, and age and sex was utilized for analysis to individually predict SCA or not using deep convolution neural network models. The base model that included age and sex, ECGs within 1 day prior to arrest, and data sampled from windows of 720 ms around the R-waves from 221 individuals with SCA and 1046 controls had an area under the receiver operat

SUBMITTER: Oberdier MT 

PROVIDER: S-EPMC11914729 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature