Atrial fibrillation risk prediction from the 12-lead electrocardiogram using digital biomarkers and deep representation learning

AIMS: This study aims to assess whether information derived from the raw 12-lead electrocardiogram (ECG) combined with clinical information is predictive of atrial fibrillation (AF) development. METHODS AND RESULTS: We use a subset of the Telehealth Network of Minas Gerais (TNMG) database consisting...

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Detalles Bibliográficos
Autores principales: Biton, Shany, Gendelman, Sheina, Ribeiro, Antônio H, Miana, Gabriela, Moreira, Carla, Ribeiro, Antonio Luiz P, Behar, Joachim A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707938/
https://www.ncbi.nlm.nih.gov/pubmed/36713102
http://dx.doi.org/10.1093/ehjdh/ztab071

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707938/
https://www.ncbi.nlm.nih.gov/pubmed/36713102
http://dx.doi.org/10.1093/ehjdh/ztab071

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