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Feham Peer-Zada, Dima Hamze and Julio Garcia
This study demonstrated the impact that heart fat can have in atrial fibrillation patients and its association with fibrillation recurrence after ablation treatment.
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Laura Arbeloa-Gómez, Jaime Álvarez-Vidal and Jose Luis Izquierdo-García
Atrial fibrillation involves an important type of heart arrhythmia caused by a lack of control in the electrical signals that arrive in the heart, produce an irregular auricular contraction, and induce blood clotting, which finally can lead to stroke. At...
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Timothy J. Hunter, Jermiah J. Joseph, Udunna Anazodo, Sanjay R. Kharche, Christopher W. McIntyre and Daniel Goldman
Background: Atrial fibrillation is a prevalent cardiac arrhythmia and may reduce cerebral blood perfusion augmenting the risk of dementia. We hypothesize that geometric variations in the cerebral arterial structure called the Circle of Willis (CoW) play ...
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Zouhair Haddi, Bouchra Ananou, Miquel Alfaras, Mustapha Ouladsine, Jean-Claude Deharo, Narcís Avellana and Stéphane Delliaux
Atrial fibrillation (AF) is still a major cause of disease morbidity and mortality, making its early diagnosis desirable and urging researchers to develop efficient methods devoted to automatic AF detection. Till now, the analysis of Holter-ECG recording...
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Hongpo Zhang, Hongzhuang Gu, Junli Gao, Peng Lu, Guanhe Chen and Zongmin Wang
Atrial fibrillation (AF) is an arrhythmia that may cause blood clots and increase the risk of stroke and heart failure. Traditional 12-lead electrocardiogram (ECG) acquisition equipment is complex and difficult to carry. Short single-lead ECG recordings ...
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Daniel Reiser, Peter Reichel, Stefan Pechmann, Maen Mallah, Maximilian Oppelt, Amelie Hagelauer, Marco Breiling, Dietmar Fey and Marc Reichenbach
In embedded applications that use neural networks (NNs) for classification tasks, it is important to not only minimize the power consumption of the NN calculation, but of the whole system. Optimization approaches for individual parts exist, such as quant...
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Yunfei Cheng, Ying Hu, Mengshu Hou, Tongjie Pan, Wenwen He and Yalan Ye
In the wearable health monitoring based on compressed sensing, atrial fibrillation detection directly from the compressed ECG can effectively reduce the time cost of data processing rather than classification after reconstruction. However, the existing m...
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Sidrah Liaqat, Kia Dashtipour, Adnan Zahid, Khaled Assaleh, Kamran Arshad and Naeem Ramzan
The atrial fibrillation (AF) is one of the most well-known cardiac arrhythmias in clinical practice, with a prevalence of 1?2% in the community, which can increase the risk of stroke and myocardial infarction. The detection of AF electrocardiogram (ECG) ...
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Junsang Park, Jin-kook Kim, Sunghoon Jung, Yeongjoon Gil, Jong-Il Choi and Ho Sung Son
Accurate electrocardiogram (ECG) interpretation is crucial in the clinical ECG workflow because it is most likely associated with a disease that can cause major problems in the body. In this study, we proposed an ECG-signal multi-classification model usi...
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Kaihao Gu, Yiheng Wang, Shengjie Yan and Xiaomei Wu
The circumferential multipolar catheter (CMC) facilitates pulmonary vein isolation (PVI) for the treatment of atrial fibrillation by catheter ablation. However, the ablation characteristics of CMC are not well understood. This study uses the finite eleme...
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