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Arrhythmias, Cardiac

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[Endogenous nocciceptin/orphanin FQ affect ischemic arrhythmias in rats through Raf kinase inhibitor protein].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To investigate whether endogenous nociceptin/orphanin FQ (N/OFQ) can inhibit arrhythmia and expression of β-adrenergic receptor (β-AR) on the surface of myocardial cell membrane in acute myocardial ischemia rats by Raf kinase inhibitory pr...

[Heartbeat-based end-to-end classification of arrhythmias].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: We propose a heartbeat-based end-to-end classification of arrhythmias to improve the classification performance for supraventricular ectopic beat (SVEB) and ventricular ectopic beat (VEB).

Spectro-Temporal Feature Based Multi-Channel Convolutional Neural Network for ECG Beat Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic classification of abnormal beats in ECG signals is crucial for monitoring cardiac conditions and the performance of the classification will improve the success rate of the treatment. However, under certain circumstances, traditional classif...

An Electrocardiogram Delineator via Deep Segmentation Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electrocardiogram (ECG) delineation is a process to detect multiple characteristic points, which contain critical diagnostic information about cardiac diseases. We treat the ECG delineation task as an one-dimensional segmentation problem, and propose...

[Automatic classification method of arrhythmia based on discriminative deep belief networks].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Existing arrhythmia classification methods usually use manual selection of electrocardiogram (ECG) signal features, so that the feature selection is subjective, and the feature extraction is complex, leaving the classification accuracy usually affect...

Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram.

JAMA cardiology
IMPORTANCE: For patients with chronic kidney disease (CKD), hyperkalemia is common, associated with fatal arrhythmias, and often asymptomatic, while guideline-directed monitoring of serum potassium is underused. A deep-learning model that enables non...

[Deep residual convolutional neural network for recognition of electrocardiogram signal arrhythmias].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Electrocardiogram (ECG) signals are easily disturbed by internal and external noise, and its morphological characteristics show significant variations for different patients. Even for the same patient, its characteristics are variable under different...

[Automatic Identifcation of Heart Block Precise Location Based on Sparse Connection Residual Network].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: To classify Right Bundle Branch Block (RBBB),Left Bundle Branch Block (LBBB) and normal ECG signals automatically.

[A DenseNet-based diagnosis algorithm for automated diagnosis using clinical ECG data].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVE: To train convolutional networks using multi-lead ECG data and classify new data accurately to provide reliable information for clinical diagnosis.