Predictors and timeline of spontaneous conversion to normal sinus rhythm: A single center retrospective cohort study of patients with symptomatic atrial fibrillation [PDF]
Indian Pacing and Electrophysiology Journal, 2023 Introduction: Annual healthcare expenditures associated with atrial fibrillation (AF) in the United States (US) continue to grow as more symptomatic patients present to emergency departments (ED).
Shubash Adhikari +5 more
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Predicting Future Incidences of Cardiac Arrhythmias Using Discrete Heartbeats from Normal Sinus Rhythm ECG Signals via Deep Learning Methods [PDF]
Diagnostics, 2023 This study aims to compare the effectiveness of using discrete heartbeats versus an entire 12-lead electrocardiogram (ECG) as the input for predicting future occurrences of arrhythmia and atrial fibrillation using deep learning models.
Yehyun Kim +7 more
doaj +2 more sources
A case of successful catheter ablation of blocked atrial bigeminy and bradycardia with the recovery of normal sinus rhythm and myocardial reverse remodeling [PDF]
Clinical Case Reports, 2022 A 69‐year‐old man presented bradycardia with a constant blocked atrial bigeminy and heart failure. Successful catheter ablation of blocked atrial bigeminy with bradycardia resulted in myocardial reverse remodeling and restoration of the normal sinus ...
Tomomi Sugiyama +5 more
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Conversion of supraventricular tachycardia to normal sinus rhythm by dexmedetomidine treatment [PDF]
Korean Journal of Anesthesiology, 2013 Cardiac dysrhythmias are an important cause of morbidity and mortality in the perioperative period, and they are more common after thoracic surgery and are most often supraventricular in origin [1]. Dexmedetomidine, a highly selective α-2 adrenoceptor agonist, is increasingly being used in anesthesia and critical care because it not only produces ...
Cheol Lee +4 more
doaj +3 more sources
Classification of atrial fibrillation and normal sinus rhythm based on convolutional neural network. [PDF]
Biomed Eng Lett, 2020 Electrocardiogram (ECG) technology plays a vital role in detecting arrhythmia. Numerous achievements have been marked in ECG-related research. Most methods first pre-process ECG signals, then extract features, and finally classify them. Most of the ECG signals used in the related studies were analyzed in specific time intervals or using a fixed number ...
Huang ML, Wu YS.
europepmc +4 more sources
Physiological Measurement, 2015 Atrial fibrillation (AF) is usually detected by inspection of the electrocardiogram waveform, a task made difficult when the signal is distorted by noise. The RR interval time series is more frequently available and accurate, yet linear and nonlinear time series analyses that detect highly varying and irregular AF are vulnerable to the common finding ...
Manuela Ferrario, Marta Carrara
exaly +3 more sources
Detecting paroxysmal atrial fibrillation from normal sinus rhythm in equine athletes using Symmetric Projection Attractor Reconstruction and machine learning [PDF]
Cardiovascular Digital Health Journal, 2022 Manasi Nandi, , Celia Marr
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Assessment of Left Ventricular Systolic Function by Cardiovascular Magnetic Resonance Compressed Sensing Real-Time Cine Imaging Combined With Area-Length Method in Normal Sinus Rhythm and Atrial Fibrillation [PDF]
Frontiers in Cardiovascular Medicine, 2022 Minjie Lu, Chen Cui, Shiqin Yu
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An Artificial Intelligence Algorithm for Early Detection of Left Ventricular Systolic Dysfunction in Patients with Normal Sinus Rhythm [PDF]
Journal of Clinical MedicineSung-Hee Song, , Young Keun On
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Comparison of the Relationship Between Inflammatory Markers and Atrial Fibrillation Burden
Anatolian Journal of Cardiology, 2023 Background: Atrial fibrillation is a complex disease with irregular ventricular response and tachycardia as a result of irregular and rapid contraction of the atria, with poor cardiovascular outcomes unless treated. Various mechanisms are involved in its
Sefa Erdi Ömür +2 more
doaj +1 more source