Cardiovascular

Arrhythmias

Latest AI and machine learning research in arrhythmias for healthcare professionals.

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Deep Learning-Based Data-Point Precise R-Peak Detection in Single-Lead Electrocardiograms.

Low-cost wearables with capability to record electrocardiograms (ECG) are becoming increasingly avai...

Nov 2021 34891392
Dual Attention Convolutional Neural Network Based on Adaptive Parametric ReLU for Denoising ECG Signals with Strong Noise.

Electrocardiogram (ECG) signal is one of the most important methods for diagnosing cardiovascular di...

Nov 2021 34891406
Improving Automatic Detection of ECG Abnormality with Less Manual Annotations using Siamese Network.

Electrocardiography is a very common, non-invasive diagnostic procedure and its interpretation is in...

Nov 2021 34891484
Segment Origin Prediction: A Self-supervised Learning Method for Electrocardiogram Arrhythmia Classification.

The automatic arrhythmia classification system has made a significant contribution to reducing the m...

Nov 2021 34891487
Increased Risks of Re-identification For Patients Posed by Deep Learning-Based ECG Identification Algorithms.

ECGs analysis is an important tool in cardiac diagnosis. ECG data also have the potential to be used...

Nov 2021 34891673
A comparative study of AI systems for epileptic seizure recognition based on EEG or ECG.

The majority of studies for automatic epileptic seizure (ictal) detection are based on electroenceph...

Nov 2021 34891722
A deep learning algorithm for detecting acute myocardial infarction.

BACKGROUND: Delayed diagnosis or misdiagnosis of acute myocardial infarction (AMI) is not unusual in...

(1)
Oct 2021 33840640
Artificial intelligence in the diagnosis and management of arrhythmias.

The field of cardiac electrophysiology (EP) had adopted simple artificial intelligence (AI) methodol...

Oct 2021 34392353
Deep learning analysis of electrocardiogram for risk prediction of drug-induced arrhythmias and diagnosis of long QT syndrome.

AIMS: Congenital long-QT syndromes (cLQTS) or drug-induced long-QT syndromes (diLQTS) can cause tors...

Oct 2021 34468739
Application of Pre-Trained Deep Learning Models for Clinical ECGs.

Automatic electrocardiogram (ECG) analysis has been one of the very early use cases for computer ass...

(1)
Sep 2021 34545818
[An arrhythmia classification method based on deep learning parallel network model].

OBJECTIVE: We propose a parallel neural network classification method to improve the performance of ...

Aug 2021 34658342
[Sleep apnea automatic detection method based on convolutional neural network].

Sleep apnea (SA) detection method based on traditional machine learning needs a lot of efforts in fe...

Aug 2021 34459167
Deep learning and the electrocardiogram: review of the current state-of-the-art.

In the recent decade, deep learning, a subset of artificial intelligence and machine learning, has b...

Aug 2021 33564873
More than meets the eye: Using AI to identify reduced heart function by electrocardiograms.

Electrocardiographic (ECG) assessment of patients with suspected heart disease is a bedrock of cardi...

Jul 2021 35590216
Mortality risk stratification using artificial intelligence-augmented electrocardiogram in cardiac intensive care unit patients.

AIMS: An artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm can identify left ve...

Jun 2021 33620440
Meeting the unmet needs of clinicians from AI systems showcased for cardiology with deep-learning-based ECG analysis.

Despite their great promise, artificial intelligence (AI) systems have yet to become ubiquitous in t...

Jun 2021 34099565
Semantic Anomaly Detection in Medical Time Series.

The main goal of this project was to define and evaluate a new unsupervised deep learning approach t...

(1)
May 2021 34042884
Artificial Intelligence Algorithm for Screening Heart Failure with Reduced Ejection Fraction Using Electrocardiography.

Although heart failure with reduced ejection fraction (HFrEF) is a common clinical syndrome and can ...

Mar 2021 33627606
A deep learning-based algorithm for detection of cortical arousal during sleep.

STUDY OBJECTIVES: The frequency of cortical arousals is an indicator of sleep quality. Additionally,...

Dec 2020 32556242
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