Deep Neural Networks Can Predict New-Onset Atrial Fibrillation From the 12-Lead ECG and Help Identify Those at Risk of Atrial Fibrillation–Related Stroke

Atrial fibrillation (AF) is associated with substantial morbidity, especially when it goes undetected. If new-onset AF could be predicted, targeted screening could be used to find it early. We hypothesized that a deep neural network could predict new-onset AF from the resting 12-lead ECG and that th...

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Detalles Bibliográficos
Autores principales: Raghunath, Sushravya, Pfeifer, John M., Ulloa-Cerna, Alvaro E., Nemani, Arun, Carbonati, Tanner, Jing, Linyuan, vanMaanen, David P., Hartzel, Dustin N., Ruhl, Jeffery A., Lagerman, Braxton F., Rocha, Daniel B., Stoudt, Nathan J., Schneider, Gargi, Johnson, Kipp W., Zimmerman, Noah, Leader, Joseph B., Kirchner, H. Lester, Griessenauer, Christoph J., Hafez, Ashraf, Good, Christopher W., Fornwalt, Brandon K., Haggerty, Christopher M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Original Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996054/
https://www.ncbi.nlm.nih.gov/pubmed/33588584
http://dx.doi.org/10.1161/CIRCULATIONAHA.120.047829

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996054/
https://www.ncbi.nlm.nih.gov/pubmed/33588584
http://dx.doi.org/10.1161/CIRCULATIONAHA.120.047829

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