Machine learning of electrophysiological signals for the prediction of ventricular arrhythmias: systematic review and examination of heterogeneity between studies

BACKGROUND: Ventricular arrhythmia (VA) precipitating sudden cardiac arrest (SCD) is among the most frequent causes of death and pose a high burden on public health systems worldwide. The increasing availability of electrophysiological signals collected through conventional methods (e.g. electrocard...

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Detalles Bibliográficos
Autores principales: Kolk, Maarten Z.H., Deb, Brototo, Ruipérez-Campillo, Samuel, Bhatia, Neil K., Clopton, Paul, Wilde, Arthur A.M., Narayan, Sanjiv M., Knops, Reinoud E., Tjong, Fleur V.Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945642/
https://www.ncbi.nlm.nih.gov/pubmed/36773349
http://dx.doi.org/10.1016/j.ebiom.2023.104462

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945642/
https://www.ncbi.nlm.nih.gov/pubmed/36773349
http://dx.doi.org/10.1016/j.ebiom.2023.104462

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