Cardiovascular

Myocardial Infarction

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

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Showing 883-903 of 6,892 articles
Dynamic coronary roadmapping via catheter tip tracking in X-ray fluoroscopy with deep learning based Bayesian filtering.

Percutaneous coronary intervention (PCI) is typically performed with image guidance using X-ray angi...

Correlation of Troponin Level (Troponin T, Troponin I) With PELOD-2 Score in Sepsis as a Predictive Factor of Mortality.

BACKGROUND: Sepsis in children with cardiovascular involvement can increase mortality. Recently, man...

A 13.34 μW Event-Driven Patient-Specific ANN Cardiac Arrhythmia Classifier for Wearable ECG Sensors.

Artificial neural network (ANN) and its variants are favored algorithm in designing cardiac arrhythm...

[Predicting atrial fibrillation through a sinus-rhythm electrocardiogram; useful or not?].

In patients with cryptogenic stroke, the detection of atrial fibrillation (AF) is important, since i...

Heartbeat classification using deep residual convolutional neural network from 2-lead electrocardiogram.

BACKGROUND: The electrocardiogram (ECG) has been widely used in the diagnosis of heart disease such ...

Predictive Monitoring of Critical Cardiorespiratory Alarms in Neonates Under Intensive Care.

We aimed at reducing alarm fatigue in neonatal intensive care units by developing a model using mach...

Automatic detection of arrhythmia from imbalanced ECG database using CNN model with SMOTE.

Timely prediction of cardiovascular diseases with the help of a computer-aided diagnosis system mini...

High Precision Digitization of Paper-Based ECG Records: A Step Toward Machine Learning.

INTRODUCTION: The electrocardiogram (ECG) plays an important role in the diagnosis of heart diseases...

ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial.

BACKGROUND: A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead ele...

Artificial Intelligence Meets Chinese Medicine.

As an interdisciplinary subject of medicine and artificial intelligence, intelligent diagnosis and t...

A Cascaded Convolutional Neural Network for Assessing Signal Quality of Dynamic ECG.

Motion artifacts and myoelectrical noise are common issues complicating the collection and processin...

Clinical Significance of Circulating Cardiomyocyte-Specific Cell-Free DNA in Patients With Heart Failure: A Proof-of-Concept Study.

We investigated clinical significance of cell-free DNA (cfDNA) in heart failure. This study enrolled...

The diagnosticity of psychophysiological signatures: Can we disentangle mental workload from acute stress with ECG and fNIRS?

The ability to identify reliable and sensitive physiological signatures of psychological dimensions ...

A speckle-tracking strain-based artificial neural network model to differentiate cardiomyopathy type.

In heart failure, invasive angiography is often employed to differentiate ischaemic from non-ischae...

ML-ResNet: A novel network to detect and locate myocardial infarction using 12 leads ECG.

BACKGROUND AND OBJECTIVE: Myocardial infarction (MI) is one of the most threatening cardiovascular d...

An Ensemble Learning Approach for Electrocardiogram Sensor Based Human Emotion Recognition.

Recently, researchers in the area of biosensor based human emotion recognition have used different t...

An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset.

To reduce the high mortality rate from cardiovascular disease (CVD), the electrocardiogram (ECG) bea...

A Multichannel Convolutional Neural Network Architecture for the Detection of the State of Mind Using Physiological Signals from Wearable Devices.

Detection of the state of mind has increasingly grown into a much favored study in recent years. Aft...

Clinical Study on Minimally Invasive Liquefaction and Drainage of Hypertensive Putaminal Hemorrhage through Frontal Approach.

 Hypertensive intracerebral hemorrhage is one of the most common cerebrovascular diseases with high...

Artificial Intelligence for Diagnosis of Acute Coronary Syndromes: A Meta-analysis of Machine Learning Approaches.

BACKGROUND: Machine learning (ML) encompasses a wide variety of methods by which artificial intellig...

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