Photoplethysmography-Based Machine Learning Approaches for Atrial Fibrillation Prediction: A Report From the Huawei Heart Study

BACKGROUND: Current wearable devices enable the detection of atrial fibrillation (AF), but a machine learning (ML)–based approach may facilitate accurate prediction of AF onset. OBJECTIVES: The present study aimed to develop, optimize, and validate an ML-based model for real-time prediction of AF on...

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Detalles Bibliográficos
Autores principales: Guo, Yutao, Wang, Hao, Zhang, Hui, Liu, Tong, Li, Luping, Liu, Lingjie, Chen, Maolin, Chen, Yundai, Lip, Gregory Y.H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9627828/
https://www.ncbi.nlm.nih.gov/pubmed/36341222
http://dx.doi.org/10.1016/j.jacasi.2021.09.004

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9627828/
https://www.ncbi.nlm.nih.gov/pubmed/36341222
http://dx.doi.org/10.1016/j.jacasi.2021.09.004

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