AIMC Topic: Arrhythmias, Cardiac

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Automated detection of arrhythmias using a novel interpretable feature set extracted from 12-lead electrocardiogram.

Computers in biology and medicine Mar 15, 2025
The availability of large-scale electrocardiogram (ECG) databases and advancements in machine learning have facilitated the development of automated diagnostic systems for cardiac arrhythmias. Deep learning models, despite their potential for high ac...
Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Algorithms Humans Databases, Factual Deep Learning
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A deep Bi-CapsNet for analysing ECG signals to classify cardiac arrhythmia.

Computers in biology and medicine Mar 13, 2025
- In recent times, the electrocardiogram (ECG) has been considered as a significant and effective screening mode in clinical practice to assess cardiac arrhythmias. Precise feature extraction and classification are considered as essential concerns in...
Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Databases, Factual Deep Learning Humans Neural Networks, Computer Algorithms
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A novel hybrid CNN-transformer model for arrhythmia detection without R-peak identification using stockwell transform.

Scientific reports Mar 6, 2025
This study presents a novel hybrid deep learning model for arrhythmia classification from electrocardiogram signals, utilizing the stockwell transform for feature extraction. As ECG signals are time-series data, they are transformed into the frequenc...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer Algorithms Deep Learning Electrocardiography
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Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BMC medical informatics and decision making Mar 3, 2025
BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The...
Humans Artificial Intelligence Pregnancy Adult Electrocardiography Arrhythmias, Cardiac Female Reproducibility of Results Young Adult Heart Rate
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Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.

Cardiovascular engineering and technology Feb 26, 2025
Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the heart's function. In the recent decade, various attempts have been made to automate the classification of electrocardiogram signals to detect heartbe...
Deep Learning Heart Rate Electrocardiography Action Potentials Databases, Factual Humans Predictive Value of Tests Reproducibility of Results Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Arrhythmias, Cardiac
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Deep Learning Approach for Automatic Heartbeat Classification.

Sensors (Basel, Switzerland) Feb 25, 2025
Arrhythmia is an irregularity in the rhythm of the heartbeat, and it is the primary method for detecting cardiac abnormalities. The electrocardiogram (ECG) identifies arrhythmias and is one of the methods used to diagnose cardiac issues. Traditional ...
Arrhythmias, Cardiac Deep Learning Humans Heart Rate Electrocardiography Algorithms Signal Processing, Computer-Assisted
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EffNet: an efficient one-dimensional convolutional neural networks for efficient classification of long-term ECG fragments.

Biomedical physics & engineering express Feb 21, 2025
Early Diagnosis of Cardiovascular disease (CVD) is essential to prevent a person from death in case of a cardiac arrhythmia. Automated ECG classification is required because manual classification by cardiologists is laborious, time-consuming, and pro...
Arrhythmias, Cardiac Electrocardiography Signal Processing, Computer-Assisted Databases, Factual Humans Cardiovascular Diseases Neural Networks, Computer Convolutional Neural Networks Algorithms
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Ventricular Arrhythmia Classification Using Similarity Maps and Hierarchical Multi-Stream Deep Learning.

IEEE transactions on bio-medical engineering Feb 20, 2025
OBJECTIVE: Ventricular arrhythmias are the primary arrhythmias that cause sudden cardiac death. We address the problem of classification between ventricular tachycardia (VT), ventricular fibrillation (VF) and non-ventricular rhythms (NVR).
Deep Learning Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Tachycardia, Ventricular Ventricular Fibrillation Humans Algorithms
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Antifreezing Ultrathin Bioionic Gel-Based Wearable System for Artificial Intelligence-Assisted Arrhythmia Diagnosis in Hypothermia.

ACS nano Feb 17, 2025
Cardiovascular disease (CAD) is a major global public health issue, with mortality rates being significantly impacted by cold temperatures. Stable and reliable electrocardiogram (ECG) monitoring in cold environments is crucial for early detection and...
Arrhythmias, Cardiac Humans Gels Artificial Intelligence Electrocardiography Hypothermia Wearable Electronic Devices Polymers
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Thermo-responsive and phase-separated hydrogels for cardiac arrhythmia diagnosis with deep learning algorithms.

Biosensors & bioelectronics Feb 14, 2025
Adhesive epidermal hydrogel electrodes are essential for achieving robust signal transduction and cardiac arrhythmia diagnosis, but detachment of conventional adhesive dressings easily causes secondary damage to delicate wound tissues due to lack of ...
Algorithms Electrodes Temperature Humans Arrhythmias, Cardiac Wearable Electronic Devices Deep Learning Hydrogels Biosensing Techniques Electrocardiography
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