Cardiovascular

Myocardial Infarction

Latest AI and machine learning research in myocardial infarction for healthcare professionals.

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Impact of artificial intelligence arrhythmia mapping on time to first ablation, procedure duration, and fluoroscopy use.

INTRODUCTION: Artificial intelligence (AI) ECG arrhythmia mapping provides arrhythmia source localiz...

The role of cell-free DNA biomarkers and patient data in the early prediction of preeclampsia: an artificial intelligence model.

BACKGROUND: Accurate individualized assessment of preeclampsia risk enables the identification of pa...

An interpretable shapelets-based method for myocardial infarction detection using dynamic learning and deep learning.

Myocardial infarction (MI) is a prevalent cardiovascular disease that contributes to global mortalit...

12-Lead ECG Reconstruction Based on Data From the First Limb Lead.

PURPOSE: Electrocardiogram (ECG) data obtained from 12 leads are the most common and informative sou...

Sleep-phasic heart rate variability predicts stress severity: Building a machine learning-based stress prediction model.

We propose a novel approach for predicting stress severity by measuring sleep phasic heart rate vari...

Predicting extremely low body weight from 12-lead electrocardiograms using a deep neural network.

Previous studies have successfully predicted overweight status by applying deep learning to 12-lead ...

ECG-only explainable deep learning algorithm predicts the risk for malignant ventricular arrhythmia in phospholamban cardiomyopathy.

BACKGROUND: Phospholamban (PLN) p.(Arg14del) variant carriers are at risk for development of maligna...

Person identification with arrhythmic ECG signals using deep convolution neural network.

Over the past decade, the use of biometrics in security systems and other applications has grown in ...

Design and hierarchical analysis of magnetic actuated robot: A governing equation based approach.

As the alternative solution to the conventional guidewire, the magnetic robot can help interventioni...

Conversational artificial intelligence: the interface with the patient concerns inventory.

The patient concerns inventory (PCI) allows patients to highlight the issues they would like to disc...

[Artificial intelligence-enhanced electrocardiography : Will it revolutionize diagnosis and management of our patients?].

The use of artificial intelligence (AI) in healthcare has made significant progress in the last 10 y...

Enhanced multimodal biometric recognition systems based on deep learning and traditional methods in smart environments.

In the field of data security, biometric security is a significant emerging concern. The multimodal ...

A Q-transform-based deep learning model for the classification of atrial fibrillation types.

According to the World Health Organization (WHO), Atrial Fibrillation (AF) is emerging as a global e...

Transforming clinical cardiology through neural networks and deep learning: A guide for clinicians.

The rapid evolution of neural networks and deep learning has revolutionized various fields, with cli...

Improving deep-learning electrocardiogram classification with an effective coloring method.

Cardiovascular diseases, particularly arrhythmias, remain a leading cause of mortality worldwide. El...

Pediatric ECG-Based Deep Learning to Predict Left Ventricular Dysfunction and Remodeling.

BACKGROUND: Artificial intelligence-enhanced ECG analysis shows promise to detect ventricular dysfun...

Identification of Atrial Fibrillation With Single-Lead Mobile ECG During Normal Sinus Rhythm Using Deep Learning.

BACKGROUND: The acquisition of single-lead electrocardiogram (ECG) from mobile devices offers a more...

Snippet Policy Network V2: Knee-Guided Neuroevolution for Multi-Lead ECG Early Classification.

Early time series classification predicts the class label of a given time series before it is comple...

Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals.

Heart diseases are leading to death across the globe. Exact detection and treatment for heart diseas...

Deep learning-based white matter lesion volume on CT is associated with outcome after acute ischemic stroke.

BACKGROUND: Intravenous thrombolysis (IVT) before endovascular treatment (EVT) for acute ischemic st...

CLINet: A novel deep learning network for ECG signal classification.

Machine learning is poised to revolutionize medicine with algorithms that spot cardiac arrhythmia. A...

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