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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...
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
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 |
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