AIMC Topic: Arrhythmias, Cardiac

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More than meets the eye: Using AI to identify reduced heart function by electrocardiograms.

Med (New York, N.Y.)
Electrocardiographic (ECG) assessment of patients with suspected heart disease is a bedrock of cardiology for diagnosing conduction system disease, arrhythmias, and heart attack. Now, using AI-assisted interpretation of ECGs, the signals within these...

Deformable US/CT Image Registration with a Convolutional Neural Network for Cardiac Arrhythmia Therapy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Image registration represents one of the fundamental techniques in medical imaging and image-guided interventions. In this paper, we present a Convolutional Neural Network (CNN) framework for deformable transesophageal US/CT image registration, for t...

Arrhythmias Classification Using Short-Time Fourier Transform and GAN Based Data Augmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Lacking sufficient training samples of different heart rhythms is a common bottleneck to obtain arrhythmias classification models with high accuracy using artificial neural networks. To solve this problem, we propose a novel data augmentation method ...

Arrhythmia Classification using Deep Learning and Machine Learning with Features Extracted from Waveform-based Signal Processing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Arrhythmia is a serious cardiovascular disease, and early diagnosis of arrhythmia is critical. In this study, we present a waveform-based signal processing (WBSP) method to produce state-of-the-art performance in arrhythmia classification. When perfo...

Wearable health devices and personal area networks: can they improve outcomes in haemodialysis patients?

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Digitization of healthcare will be a major innovation driver in the coming decade. Also, enabled by technological advancements and electronics miniaturization, wearable health device (WHD) applications are expected to grow exponentially. This, in tur...

Contribution of neural networks in the diagnosis and treatment of cardiac arrhythmia.

Discovery medicine
Arrhythmia is a dangerous disease in which the heart rhythm varies and it may be very fast or very slow. Rapid heartbeats can lead to shortness of breath, chest pain, and sudden weakness, whereas slow heartbeats can lead to dizziness, problems with c...

[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...