Cargando…
The 12-lead electrocardiogram as a biomarker of biological age
BACKGROUND: We have demonstrated that a neural network is able to predict a person’s age from the electrocardiogram (ECG) [artificial intelligence (AI) ECG age]. However, some discrepancies were observed between ECG-derived and chronological ages. We assessed whether the difference between AI ECG an...
Autores principales: | Ladejobi, Adetola O, Medina-Inojosa, Jose R, Shelly Cohen, Michal, Attia, Zachi I, Scott, Christopher G, LeBrasseur, Nathan K, Gersh, Bernard J, Noseworthy, Peter A, Friedman, Paul A, Kapa, Suraj, Lopez-Jimenez, Francisco |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707884/ https://www.ncbi.nlm.nih.gov/pubmed/36713596 http://dx.doi.org/10.1093/ehjdh/ztab043 |
Ejemplares similares
-
Real-world performance, long-term efficacy, and absence of bias in the artificial intelligence enhanced electrocardiogram to detect left ventricular systolic dysfunction
por: Harmon, David M, et al.
Publicado: (2022) -
Automated detection of low ejection fraction from a one-lead electrocardiogram: application of an AI algorithm to an electrocardiogram-enabled Digital Stethoscope( )
por: Attia, Zachi I, et al.
Publicado: (2022) -
Digital health innovation in cardiology
por: Ladejobi, Adetola O., et al.
Publicado: (2020) -
Electrocardiogram-Artificial Intelligence and Immune-Mediated Necrotizing Myopathy: Predicting Left Ventricular Dysfunction and Clinical Outcomes
por: Klein, Christopher J., et al.
Publicado: (2022) -
Noninvasive assessment of dofetilide plasma concentration using a deep learning (neural network) analysis of the surface electrocardiogram: A proof of concept study
por: Attia, Zachi I., et al.
Publicado: (2018)