AIMC Topic: Arrhythmias, Cardiac

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Evaluation of antiarrhythmia drug through QSPR modeling and multi criteria decision analysis.

Scientific reports Aug 9, 2025
This study explores how topological indices (TIs), which are mathematical descriptors of a drug's molecular structure, can support to predict vital properties and biological activities. This understanding is a key for more effective drug design. We f...
Models, Molecular Anti-Arrhythmia Agents Arrhythmias, Cardiac Quantitative Structure-Activity Relationship Humans Decision Support Techniques
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Investigating the Impact of the Stationarity Hypothesis on Heart Failure Detection using Deep Convolutional Scattering Networks and Machine Learning.

Scientific reports Jul 31, 2025
Detection of Cardiovascular Diseases (CVDs) has become crucial nowadays, as the World Health Organization (WHO) declares CVDs as the major leading causes of death in the globe. Moreover, the death rate due to CVDs is expected to rise in the next few ...
Electrocardiography Signal Processing, Computer-Assisted Heart Failure Arrhythmias, Cardiac Machine Learning Algorithms Deep Learning Humans
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Fusion of Personalized Federated Learning (PFL) with Differential Privacy (DP) Learning for Diagnosis of Arrhythmia Disease.

PloS one Jul 11, 2025
This paper presents a novel privacy-preserving architecture, a fusion of Federated Learning with Personalized Models and Differential Privacy (FLPMDP), for diagnosing arrhythmia from 12-lead electrocardiogram (ECG) signals. The architecture supports ...
Machine Learning Algorithms Electrocardiography Privacy Humans Arrhythmias, Cardiac Federated Learning
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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...
Deep Learning Convolutional Neural Networks Electrocardiography Neural Networks, Computer Algorithms Databases, Factual Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans
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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...
Action Potentials Reproducibility of Results Predictive Value of Tests Humans Deep Learning Arrhythmias, Cardiac Neural Networks, Computer Electrocardiography Heart Rate Computer Simulation Models, Cardiovascular Body Surface Potential Mapping Electrophysiologic Techniques, Cardiac
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Unveiling fetal heart health: harnessing auto-metric graph neural networks and Hazelnut tree search for ECG-based arrhythmia detection.

Computer methods in biomechanics and biomedical engineering Apr 24, 2025
Fetal electrocardiogram (ECG) provides a non-invasive means to assess fetal heart health, but isolating the fetal signal from the dominant maternal ECG remains challenging. This study introduces the FHH-AMGNN-HTSOA-ECG-AD method for enhanced fetal ar...
Signal Processing, Computer-Assisted Neural Networks, Computer Arrhythmias, Cardiac Algorithms Wavelet Analysis Humans Fetal Heart Pregnancy Female Electrocardiography Graph Neural Networks
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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...
Atrial Fibrillation Female Aged Sensitivity and Specificity Humans Artificial Intelligence Algorithms ROC Curve Electrocardiography Heart Failure Arrhythmias, Cardiac Male Middle Aged Deep Learning
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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...
Male Middle Aged Convolutional Neural Networks Atrial Fibrillation Electrocardiography, Ambulatory Arrhythmias, Cardiac Algorithms Female Aged Humans Neural Networks, Computer
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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 Diagnosis, Computer-Assisted Machine Learning Predictive Value of Tests Electrocardiography Algorithms Heart Rate Action Potentials Reproducibility of Results Signal Processing, Computer-Assisted Arrhythmias, Cardiac
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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...
Electrocardiography Area Under Curve Electroencephalography Coma Arrhythmias, Cardiac Heart Arrest Male Middle Aged ROC Curve Female Aged Adult Machine Learning Prognosis Humans
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