Myocardial Infarction

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Cardiology Subcategories: Acute Coronary Syndrome Arrhythmias Atherosclerosis Congestive Heart Failure Dyslipidemia Hypertension Metabolic Syndrome Myocardial Infarction PCI Peripheral Artery Disease Prevention Strokes Venous Thrombosis

Showing 967-987 of 7,963 articles

Machine learning versus traditional methods for the development of risk stratification scores: a case study using original Canadian Syncope Risk Score data.

Artificial Intelligence and machine learning (ML) methods are promising for risk-stratification, but...

Nov 2021 34734350

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

Electrocardiogram (ECG) indicates the occurrence of various cardiac diseases, and the accurate class...

Oct 2021 34718933

Rational and design of ST-segment elevation not associated with acute cardiac necrosis (LESTONNAC). A prospective registry for validation of a deep learning system assisted by artificial intelligence.

BACKGROUND: Patients with chest pain and persistent ST segment elevation (STE) may not have acute co...

Oct 2021 34763217

Review of Deep Learning-Based Atrial Fibrillation Detection Studies.

Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and prematur...

Oct 2021 34769819

Unpaired MR Motion Artifact Deep Learning Using Outlier-Rejecting Bootstrap Aggregation.

Recently, deep learning approaches for MR motion artifact correction have been extensively studied. ...

Oct 2021 34133276

A Novel Prediction Model of Acute Kidney Injury Based on Combined Blood Variables in STEMI.

BACKGROUND: Development of acute kidney injury (AKI) is associated with poor prognosis in patients w...

Oct 2021 36341223

Robustness of convolutional neural networks to physiological electrocardiogram noise.

The electrocardiogram (ECG) is a widespread diagnostic tool in healthcare and supports the diagnosis...

Oct 2021 34689617

Optimal ECG-lead selection increases generalizability of deep learning on ECG abnormality classification.

Deep learning (DL) has achieved promising performance in detecting common abnormalities from the 12-...

Oct 2021 34689629

Intentional Observational Clinical Research Design: Innovative Design for Complex Clinical Research Using Advanced Technology.

The growing use of robots in nursing and healthcare facilities has prompted increasing research on h...

Oct 2021 34769703

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram.

Computerized interpretation of electrocardiogram plays an important role in daily cardiovascular hea...

Oct 2021 34677739

Classification of Arrhythmia in Heartbeat Detection Using Deep Learning.

The electrocardiogram (ECG) is one of the most widely used diagnostic instruments in medicine and he...

Oct 2021 34712316

The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition.

BACKGROUND: Type 1 Brugada syndrome (BrS) is a hereditary arrhythmogenic disease showing peculiar el...

Oct 2021 34645390

ML-Net: Multi-Channel Lightweight Network for Detecting Myocardial Infarction.

Due to the complexity of myocardial infarction (MI) waveform, most traditional automatic diagnosis m...

Oct 2021 33606647

A Deep-Learning Algorithm-Enhanced System Integrating Electrocardiograms and Chest X-rays for Diagnosing Aortic Dissection.

BACKGROUND: Chest pain is the most common symptom of aortic dissection (AD), but it is often confuse...

Oct 2021 34619339

Information fusion and multi-classifier system for miner fatigue recognition in plateau environments based on electrocardiography and electromyography signals.

BACKGROUND AND OBJECTIVE: Human factors are important contributors to accidents, especially human er...

Oct 2021 34644668

Paroxysmal atrial fibrillation prediction based on morphological variant P-wave analysis with wideband ECG and deep learning.

BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is one of the most frequent asymptomatic arrhythm...

Sep 2021 34592687

Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals-Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study.

BACKGROUND: When using a smartwatch to obtain electrocardiogram (ECG) signals from multiple leads, t...

Sep 2021 34505839

Cardiovascular

Browse Categories

Machine learning versus traditional methods for the development of risk stratification scores: a case study using original Canadian Syncope Risk Score data.

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

Rational and design of ST-segment elevation not associated with acute cardiac necrosis (LESTONNAC). A prospective registry for validation of a deep learning system assisted by artificial intelligence.

Review of Deep Learning-Based Atrial Fibrillation Detection Studies.

Unpaired MR Motion Artifact Deep Learning Using Outlier-Rejecting Bootstrap Aggregation.

A Novel Prediction Model of Acute Kidney Injury Based on Combined Blood Variables in STEMI.

Robustness of convolutional neural networks to physiological electrocardiogram noise.

Optimal ECG-lead selection increases generalizability of deep learning on ECG abnormality classification.

Intentional Observational Clinical Research Design: Innovative Design for Complex Clinical Research Using Advanced Technology.

A community effort to assess and improve computerized interpretation of 12-lead resting electrocardiogram.

Classification of Arrhythmia in Heartbeat Detection Using Deep Learning.

The BrAID study protocol: integration of machine learning and transcriptomics for brugada syndrome recognition.

ML-Net: Multi-Channel Lightweight Network for Detecting Myocardial Infarction.

A Deep-Learning Algorithm-Enhanced System Integrating Electrocardiograms and Chest X-rays for Diagnosing Aortic Dissection.

Information fusion and multi-classifier system for miner fatigue recognition in plateau environments based on electrocardiography and electromyography signals.

Paroxysmal atrial fibrillation prediction based on morphological variant P-wave analysis with wideband ECG and deep learning.

ECG-based machine-learning algorithms for heartbeat classification.

Hyperglycemia Identification Using ECG in Deep Learning Era.

Deep learning model to detect significant aortic regurgitation using electrocardiography.

ECG data dependency for atrial fibrillation detection based on residual networks.

Automated Detection of Acute Myocardial Infarction Using Asynchronous Electrocardiogram Signals-Preview of Implementing Artificial Intelligence With Multichannel Electrocardiographs Obtained From Smartwatches: Retrospective Study.

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