Application of a machine learning algorithm for detection of atrial fibrillation in secondary care

Application of a machine learning algorithm for detection of atrial fibrillation in secondary care

Atrial fibrillation (AF) is the most common sustained heart arrhythmia and significantly increases risk of stroke. Opportunistic AF testing in high-risk patients typically requires frequent electrocardiogram tests to capture the arrhythmia. Risk-prediction algorithms may help to more accurately iden...

Full description

Bibliographic Details
Main Authors: Kevin G. Pollock, Sara Sekelj, Ellie Johnston, Belinda Sandler, Nathan R. Hill, Fu Siong Ng, Sadia Khan, Ayman Nassar, Usman Farooqui
Format: Article
Language:English
Published: Elsevier 2020-12-01
Series:International Journal of Cardiology: Heart & Vasculature
Subjects:
Atrial fibrillation
Machine learning
Artificial intelligence
Diagnosis
Online Access:http://www.sciencedirect.com/science/article/pii/S2352906720303729

Internet

http://www.sciencedirect.com/science/article/pii/S2352906720303729

Similar Items