Application of a convolutional neural network for predicting the occurrence of ventricular tachyarrhythmia using heart rate variability features

Predicting the occurrence of ventricular tachyarrhythmia (VTA) in advance is a matter of utmost importance for saving the lives of cardiac arrhythmia patients. Machine learning algorithms have been used to predict the occurrence of imminent VTA. In this study, we used a one-dimensional convolutional...

Descripción completa

Detalles Bibliográficos
Autores principales: Taye, Getu Tadele, Hwang, Han-Jeong, Lim, Ki Moo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7174382/
https://www.ncbi.nlm.nih.gov/pubmed/32317680
http://dx.doi.org/10.1038/s41598-020-63566-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7174382/
https://www.ncbi.nlm.nih.gov/pubmed/32317680
http://dx.doi.org/10.1038/s41598-020-63566-8

Ejemplares similares