AIMC Topic: Arrhythmias, Cardiac

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Arrhythmia classification based on multi-input convolutional neural network with attention mechanism.

PloS one Jun 17, 2025
Arrhythmia is a prevalent cardiac disorder that can lead to severe complications such as stroke and cardiac arrest. While deep learning has advanced automated ECG analysis, challenges remain in accurately classifying arrhythmias due to signal variabi...
Humans Neural Networks, Computer Algorithms Convolutional Neural Networks Databases, Factual Electrocardiography Signal Processing, Computer-Assisted Deep Learning Arrhythmias, Cardiac
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Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem.

BMC cardiovascular disorders Apr 28, 2025
BACKGROUND: The risk stratification and prognosis of cardiac arrhythmia depend on the individual condition of patients, while invasive diagnostic methods may be risky to patient health, and current non-invasive diagnostic methods are applicable to fe...
Heart Rate Models, Cardiovascular Body Surface Potential Mapping Electrophysiologic Techniques, Cardiac Action Potentials Predictive Value of Tests Arrhythmias, Cardiac Reproducibility of Results Deep Learning Electrocardiography Humans Neural Networks, Computer Computer Simulation
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Development of an Artificial Intelligence-Enabled Electrocardiography to Detect 23 Cardiac Arrhythmias and Predict Cardiovascular Outcomes.

Journal of medical systems Apr 22, 2025
Arrhythmias are common and can affect individuals with or without structural heart disease. Deep learning models (DLMs) have shown the ability to recognize arrhythmias using 12-lead electrocardiograms (ECGs). However, the limited types of arrhythmias...
Humans Artificial Intelligence Deep Learning ROC Curve Electrocardiography Atrial Fibrillation Heart Failure Arrhythmias, Cardiac Sensitivity and Specificity Male Middle Aged Algorithms Female Aged
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A hybrid machine learning approach using particle swarm optimization for cardiac arrhythmia classification.

International journal of cardiology Apr 11, 2025
BACKGROUND: Precise and rapid identification of cardiac arrhythmias is paramount for delivering optimal patient care. Machine learning (ML) techniques hold significant promise for classifying arrhythmias, yet achieving peak performance often necessit...
Arrhythmias, Cardiac Particle Swarm Optimization Machine Learning Algorithms Electrocardiography Humans
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Assessment of the long RR intervals using convolutional neural networks in single-lead long-term Holter electrocardiogram recordings.

Scientific reports Apr 7, 2025
Advancements in medical technology have extended long-term electrocardiogram (ECG) monitoring from the traditional 24 h to 7-14 days, significantly enriching ECG data. However, this poses unprecedented challenges for physicians in analyzing these ext...
Atrial Fibrillation Convolutional Neural Networks Electrocardiography, Ambulatory Arrhythmias, Cardiac Neural Networks, Computer Algorithms Female Aged Male Middle Aged Humans
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ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

BMC cardiovascular disorders Apr 7, 2025
A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly imp...
Humans Machine Learning Electrocardiography Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Algorithms Reproducibility of Results Diagnosis, Computer-Assisted Arrhythmias, Cardiac Heart Rate
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Explainable machine learning model based on EEG, ECG, and clinical features for predicting neurological outcomes in cardiac arrest patient.

Scientific reports Apr 3, 2025
Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest is critical for informed clinical decision-making. Existing studies have predominantly focused on EEG for assessing brain injury, with some exploring...
Coma Electroencephalography Arrhythmias, Cardiac Heart Arrest Aged Adult Male Electrocardiography Area Under Curve Middle Aged Machine Learning ROC Curve Prognosis Female Humans
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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...
Arrhythmias, Cardiac Deep Learning Humans Electrocardiography Signal Processing, Computer-Assisted Algorithms Databases, Factual
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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 Humans Arrhythmias, Cardiac Neural Networks, Computer Algorithms Databases, Factual Deep Learning
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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...
Humans Neural Networks, Computer Algorithms Arrhythmias, Cardiac Deep Learning Electrocardiography Signal Processing, Computer-Assisted
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