Predicting atrial fibrillation in primary care using machine learning.

Predicting atrial fibrillation in primary care using machine learning.

BACKGROUND:Atrial fibrillation (AF) is the most common sustained heart arrhythmia. However, as many cases are asymptomatic, a large proportion of patients remain undiagnosed until serious complications arise. Efficient, cost-effective detection of the undiagnosed may be supported by risk-prediction...

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Bibliographic Details
Main Authors: Nathan R Hill, Daniel Ayoubkhani, Phil McEwan, Daniel M Sugrue, Usman Farooqui, Steven Lister, Matthew Lumley, Ameet Bakhai, Alexander T Cohen, Mark O'Neill, David Clifton, Jason Gordon
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0224582

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