Cardiovascular

Myocardial Infarction

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

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Applying Recurrent Neural Networks for Anomaly Detection in Electrocardiogram Sensor Data.

Monitoring heart electrical activity is an effective way of detecting existing and developing condit...

SEResUTer: a deep learning approach for accurate ECG signal delineation and atrial fibrillation detection.

Accurate detection of electrocardiogram (ECG) waveforms is crucial for computer-aided diagnosis of c...

Personalized ECG monitoring and adaptive machine learning.

This non-technical review introduces key concepts in personalized ECG monitoring (pECG), which aims ...

Deep learning-based dynamic ventilatory threshold estimation from electrocardiograms.

BACKGROUND AND OBJECTIVE: The ventilatory threshold (VT) marks the transition from aerobic to anaero...

Artificial intelligence-enhanced electrocardiogram for arrhythmogenic right ventricular cardiomyopathy detection.

AIMS: ECG abnormalities are often the first signs of arrhythmogenic right ventricular cardiomyopathy...

Impact of automatic acquisition of key clinical information on the accuracy of electrocardiogram interpretation: a cross-sectional study.

BACKGROUND: The accuracy of electrocardiogram (ECG) interpretation by doctors are affected by the av...

Does artificial intelligence enhance physician interpretation of optical coherence tomography: insights from eye tracking.

BACKGROUND AND OBJECTIVES: The adoption of optical coherence tomography (OCT) in percutaneous corona...

Learning Skill Characteristics From Manipulations.

Percutaneous coronary intervention (PCI) has increasingly become the main treatment for coronary art...

Deep learning-based regional ECG diagnosis platform.

OBJECTIVE: To enable the intelligent diagnosis of a variety of common Electrocardiogram (ECG), we in...

ECG-Based Multiclass Arrhythmia Classification Using Beat-Level Fusion Network.

Cardiovascular disease (CVD) is one of the most severe diseases threatening human life. Electrocardi...

International evaluation of an artificial intelligence-powered electrocardiogram model detecting acute coronary occlusion myocardial infarction.

AIMS: A majority of acute coronary syndromes (ACS) present without typical ST elevation. One-third o...

Deep learning with fetal ECG recognition.

Independent component analysis (ICA) is widely used in the extraction of fetal ECG (FECG). However, ...

Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.

OBJECTIVES: The biomarker N-terminal pro B-type natriuretic peptide (NT-proBNP) has predictive value...

Wavelet transform and deep learning-based obstructive sleep apnea detection from single-lead ECG signals.

Sleep apnea is a common sleep disorder. Traditional testing and diagnosis heavily rely on the expert...

A deep learning analysis of stroke onset time prediction and comparison to DWI-FLAIR mismatch.

INTRODUCTION: When time since stroke onset is unknown, DWI-FLAIR mismatch rating is an established t...

Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.

OBJECTIVE: This study aimed to determine the feasibility and limitations of deep learning-based coro...

Deep Learning Models for Predicting Left Heart Abnormalities From Single-Lead Electrocardiogram for the Development of Wearable Devices.

BACKGROUND: Left heart abnormalities are risk factors for heart failure. However, echocardiography i...

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