AIMC Topic: Arrhythmias, Cardiac

Clear Filters Showing 131 to 140 of 287 articles

Efficacy and Safety of Appropriate Shocks and Antitachycardia Pacing in Transvenous and Subcutaneous Implantable Defibrillators: Analysis of All Appropriate Therapy in the PRAETORIAN Trial.

Circulation Nov 14, 2021
BACKGROUND: The PRAETORIAN trial (A Prospective, Randomized Comparison of Subcutaneous and Transvenous Implantable Cardioverter Defibrillator Therapy) showed noninferiority of subcutaneous implantable cardioverter defibrillator (S-ICD) compared with ...
Middle Aged Female Defibrillators, Implantable Aged Treatment Outcome Arrhythmias, Cardiac Male Humans Prospective Studies
View on PubMed DOI

Classification of electrocardiogram signals with waveform morphological analysis and support vector machines.

Medical & biological engineering & computing Oct 30, 2021
Electrocardiogram (ECG) indicates the occurrence of various cardiac diseases, and the accurate classification of ECG signals is important for the automatic diagnosis of arrhythmia. This paper presents a novel classification method based on multiple f...
Humans Algorithms Signal Processing, Computer-Assisted Arrhythmias, Cardiac Electrocardiography Wavelet Analysis Support Vector Machine
View on PubMed DOI

Classification of Arrhythmia in Heartbeat Detection Using Deep Learning.

Computational intelligence and neuroscience Oct 19, 2021
The electrocardiogram (ECG) is one of the most widely used diagnostic instruments in medicine and healthcare. Deep learning methods have shown promise in healthcare prediction challenges involving ECG data. This paper aims to apply deep learning tech...
Deep Learning Electrocardiography Arrhythmias, Cardiac Neural Networks, Computer Algorithms Humans Heart Rate
View on PubMed DOI

Machine learning-based risk prediction of malignant arrhythmia in hospitalized patients with heart failure.

ESC heart failure Sep 28, 2021
AIMS: Predicting the risk of malignant arrhythmias (MA) in hospitalized patients with heart failure (HF) is challenging. Machine learning (ML) can handle a large volume of complex data more effectively than traditional statistical methods. This study...
Female Heart Failure Humans ROC Curve Machine Learning Logistic Models Arrhythmias, Cardiac
View on PubMed DOI

Application of a time-series deep learning model to predict cardiac dysrhythmias in electronic health records.

PloS one Sep 13, 2021
BACKGROUND: Cardiac dysrhythmias (CD) affect millions of Americans in the United States (US), and are associated with considerable morbidity and mortality. New strategies to combat this growing problem are urgently needed.
Bayes Theorem Arrhythmias, Cardiac Middle Aged Deep Learning United States Aged Male Humans Neural Networks, Computer Electronic Health Records Female
View on PubMed DOI

Machine Learning for Real-Time Heart Disease Prediction.

IEEE journal of biomedical and health informatics Sep 3, 2021
Heart-related anomalies are among the most common causes of death worldwide. Patients are often asymptomatic until a fatal event happens, and even when they are under observation, trained personnel is needed in order to identify a heart anomaly. In t...
Machine Learning Heart Diseases Algorithms Electrocardiography Humans Arrhythmias, Cardiac
View on PubMed DOI

Interpretation of Electrocardiogram Heartbeat by CNN and GRU.

Computational and mathematical methods in medicine Aug 29, 2021
The diagnosis of electrocardiogram (ECG) is extremely onerous and inefficient, so it is necessary to use a computer-aided diagnosis of ECG signals. However, it is still a challenging problem to design high-accuracy ECG algorithms suitable for the med...
Wavelet Analysis Neural Networks, Computer Algorithms Humans Electrocardiography Signal Processing, Computer-Assisted Deep Learning Heart Rate Databases, Factual Wearable Electronic Devices Monitoring, Ambulatory Diagnosis, Computer-Assisted Arrhythmias, Cardiac Computational Biology
View on PubMed DOI

LwF-ECG: Learning-without-forgetting approach for electrocardiogram heartbeat classification based on memory with task selector.

Computers in biology and medicine Aug 27, 2021
Most existing Electrocardiogram (ECG) classification methods assume that all arrhythmia classes are known during the training phase. In this paper, the problem of learning several successive tasks is addressed, where, in each new task, there are new ...
Humans Electrocardiography Arrhythmias, Cardiac Heart Rate Neural Networks, Computer Machine Learning
View on PubMed DOI

Deep learning methods for screening patients' S-ICD implantation eligibility.

Artificial intelligence in medicine Aug 9, 2021
Subcutaneous Implantable Cardioverter-Defibrillators (S-ICDs) are used for prevention of sudden cardiac death triggered by ventricular arrhythmias. T Wave Over Sensing (TWOS) is an inherent risk with S-ICDs which can lead to inappropriate shocks. A m...
Defibrillators, Implantable Death, Sudden, Cardiac Mass Screening Arrhythmias, Cardiac Deep Learning Electrocardiography Humans
View on PubMed DOI

xECGNet: Fine-tuning attention map within convolutional neural network to improve detection and explainability of concurrent cardiac arrhythmias.

Computer methods and programs in biomedicine Jul 21, 2021
Background and objectiveDetecting abnormal patterns within an electrocardiogram (ECG) is crucial for diagnosing cardiovascular diseases. We start from two unresolved problems in applying deep-learning-based ECG classification models to clinical pract...
Arrhythmias, Cardiac Attention Neural Networks, Computer Algorithms Electrocardiography Humans
View on PubMed DOI
Popular Topics
Recent Journals