Assessment of the atrial fibrillation burden in Holter ECG recordings using artificial intelligence

FUNDING ACKNOWLEDGEMENTS: Type of funding sources: Foundation. Main funding source(s): Swiss National Science Foundation, Swiss Heart Foundation BACKGROUND: Emerging evidence indicates that a high atrial fibrillation (AF) burden is associated with adverse outcome. However, AF burden is not routinely...

Descripción completa

Detalles Bibliográficos
Autores principales: Hennings, E, Coslovsky, M, Paladini, R E, Aeschbacher, S, Knecht, S, Schlageter, V, Krisai, P, Badertscher, P, Sticherling, C, Osswald, S, Kuehne, M, Zuern, C S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
38.3 - Artificial Intelligence (Machine Learning, Deep Learning)
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10207033/
http://dx.doi.org/10.1093/europace/euad122.528

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10207033/
http://dx.doi.org/10.1093/europace/euad122.528

Ejemplares similares