Back to Search Start Over

Artificial intelligence-enhanced electrocardiography for the identification of a sex-related cardiovascular risk continuum: a retrospective cohort study

Authors :
Sau, Arunashis
Sieliwonczyk, Ewa
Patlatzoglou, Konstantinos
Pastika, Libor
McGurk, Kathryn A
Ribeiro, Antônio H
Ribeiro, Antonio Luiz P
Ho, Jennifer E
Peters, Nicholas S
Ware, James S
Tayal, Upasana
Kramer, Daniel B
Waks, Jonathan W
Ng, Fu Siong
Source :
The Lancet Digital Health; March 2025, Vol. 7 Issue: 3 pe184-e194, 11p
Publication Year :
2025

Abstract

Females are typically underserved in cardiovascular medicine. The use of sex as a dichotomous variable for risk stratification fails to capture the heterogeneity of risk within each sex. We aimed to develop an artificial intelligence-enhanced electrocardiography (AI-ECG) model to investigate sex-specific cardiovascular risk.

Details

Language :
English
ISSN :
25897500
Volume :
7
Issue :
3
Database :
Supplemental Index
Journal :
The Lancet Digital Health
Publication Type :
Periodical
Accession number :
ejs69139412
Full Text :
https://doi.org/10.1016/j.landig.2024.12.003