AIMC Topic: Electrocardiography

Clear Filters Showing 51 to 60 of 1286 articles

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...
Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans Neural Networks, Computer Algorithms Deep Learning
View on PubMed DOI

Deep learning based estimation of heart surface potentials.

Artificial intelligence in medicine Mar 5, 2025
Electrocardiographic imaging (ECGI) aims to noninvasively estimate heart surface potentials starting from body surface potentials. This is classically based on geometric information on the torso and the heart from imaging, which complicates clinical ...
Humans Female Male Deep Learning Electrocardiography Heart Body Surface Potential Mapping
View on PubMed DOI

Joint fusion of EHR and ECG data using attention-based CNN and ViT for predicting adverse clinical endpoints in percutaneous coronary intervention patients.

Computers in biology and medicine Mar 5, 2025
Predicting post-Percutaneous Coronary Intervention (PCI) outcomes is crucial for effective patient management and quality improvement in healthcare. However, achieving accurate predictions requires the integration of multimodal clinical data, includi...
Percutaneous Coronary Intervention Male Middle Aged Electrocardiography Female Aged Humans Neural Networks, Computer Electronic Health Records
View on PubMed DOI

Classifying metro drivers' cognitive distractions during manual operations using machine learning and random forest-recursive feature elimination.

Scientific reports Mar 4, 2025
Metro drivers are more likely to trigger accidents if they suffer from cognitive distractions during manual driving. However, identifying metro drivers' cognitive distractions faces challenges as generally no obvious behavior can be found during the ...
Random Forest Attention Heart Rate Male Cognition Electrocardiography Automobile Driving Humans Machine Learning Algorithms Female Adult
View on PubMed DOI

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...
Pregnancy Female Reproducibility of Results Humans Artificial Intelligence Electrocardiography Arrhythmias, Cardiac Heart Rate Young Adult Adult
View on PubMed DOI

MLFusion: Multilevel Data Fusion using CNNs for atrial fibrillation detection.

Computers in biology and medicine Mar 1, 2025
Data fusion, involving the simultaneous integration of signals from multiple sensors, is an emerging field that facilitates more accurate inferences in instrumentation applications. This paper presents a novel fusion methodology for multi-sensor mult...
Atrial Fibrillation Humans Photoplethysmography Neural Networks, Computer Electrocardiography Databases, Factual Signal Processing, Computer-Assisted
View on PubMed DOI

Deep Learning-Based Electrocardiogram Model (EIANet) to Predict Emergency Department Cardiac Arrest: Development and External Validation Study.

Journal of medical Internet research Feb 28, 2025
BACKGROUND: In-hospital cardiac arrest (IHCA) is a severe and sudden medical emergency that is characterized by the abrupt cessation of circulatory function, leading to death or irreversible organ damage if not addressed immediately. Emergency depart...
Aged Adult Heart Arrest Male Humans Electrocardiography Middle Aged Female Triage Deep Learning Emergency Service, Hospital
View on PubMed DOI

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...
Reproducibility of Results Signal Processing, Computer-Assisted Diagnosis, Computer-Assisted Arrhythmias, Cardiac Humans Deep Learning Electrocardiography Heart Rate Databases, Factual Action Potentials Predictive Value of Tests
View on PubMed DOI

A Novel Framework for Quantum-Enhanced Federated Learning with Edge Computing for Advanced Pain Assessment Using ECG Signals via Continuous Wavelet Transform Images.

Sensors (Basel, Switzerland) Feb 26, 2025
Our research introduces a framework that integrates edge computing, quantum transfer learning, and federated learning to revolutionize pain level assessment through ECG signal analysis. The primary focus lies in developing a robust, privacy-preservin...
Signal Processing, Computer-Assisted Pain Wavelet Analysis Electrocardiography Pain Measurement Humans Neural Networks, Computer Federated Learning Machine Learning Algorithms
View on PubMed DOI

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 Heart Rate Deep Learning Humans Algorithms Electrocardiography Signal Processing, Computer-Assisted
View on PubMed DOI
Popular Topics
Recent Journals