Automatic online detection of atrial fibrillation based on symbolic dynamics and Shannon entropy-Reference-Cited by-同舟云学术

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Automatic online detection of atrial fibrillation based on symbolic dynamics and Shannon entropy

Published:2014 Issue:1 Volume:13 Page:18
ISSN:1475-925X
Container-title:BioMedical Engineering OnLine
language:en
Short-container-title:BioMedical Engineering OnLine

Author:

Zhou Xiaolin,Ding Hongxia,Ung Benjamin,Pickwell-MacPherson Emma,Zhang Yuanting

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,Biomedical Engineering,General Medicine,Biomaterials,Radiological and Ultrasound Technology

Reference13 articles.

1. Atrial fibrillation: Mechanistic insights and treatment options

2. ACC/AHA/ESC guidelines for the management of patients with atrial fibrillation: executive summary

3. Effect of Intensity of Oral Anticoagulation on Stroke Severity and Mortality in Atrial Fibrillation

4. Secular Trends in Incidence of Atrial Fibrillation in Olmsted County, Minnesota, 1980 to 2000, and Implications on the Projections for Future Prevalence

5. Association of Atrial Fibrillation and Obstructive Sleep Apnea

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1. Multiscale dilated convolutional neural network for Atrial Fibrillation detection;PLOS ONE;2024-06-03

2. A generalizable and robust deep learning method for atrial fibrillation detection from long-term electrocardiogram;Biomedical Signal Processing and Control;2024-04

3. Continuous Atrial Fibrillation Monitoring From Photoplethysmography;JACC: Clinical Electrophysiology;2024-02

4. A System Detection of Atrial Fibrillation Using One ECG Derivation and Inductive Transfer Learning;IFMBE Proceedings;2024

5. Detection of Atrial Fibrillation using a Feedforward Sequential Model;International Journal of Technology;2023-12-07

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