Myocardial Infarction

Artificial intelligence-based diagnosis of acute pulmonary embolism: Development of a machine learning model using 12-lead electrocardiogram.

INTRODUCTION: Pulmonary embolism (PE) is a life-threatening condition, in which diagnostic uncertain...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Background Statins are guideline-recommended medications that reduce cardiovascular events in patien...

Novel AI-based HRV analysis (NAIHA) in healthcare automation and related applications.

BACKGROUND: Heart rate variability (HRV) analysis computed on R-R interval series of ECG records wit...

An ECG Stitching Scheme for Driver Arrhythmia Classification Based on Deep Learning.

This study proposes an electrocardiogram (ECG) signal stitching scheme to detect arrhythmias in driv...

CVD22: Explainable artificial intelligence determination of the relationship of troponin to D-Dimer, mortality, and CK-MB in COVID-19 patients.

BACKGROUND AND PURPOSE: COVID-19, which emerged in Wuhan (China), is one of the deadliest and fastes...

Convolutional Neural Network for Individual Identification Using Phase Space Reconstruction of Electrocardiogram.

Electrocardiogram (ECG) biometric provides an authentication to identify an individual on the basis ...

Correlation analysis of deep learning methods in S-ICD screening.

BACKGROUND: Machine learning methods are used in the classification of various cardiovascular diseas...

Comparison of two artificial intelligence-augmented ECG approaches: Machine learning and deep learning.

BACKGROUND: Artificial intelligence-augmented ECG (AI-ECG) refers to the application of novel AI sol...

ECG signal feature extraction trends in methods and applications.

Signal analysis is a domain which is an amalgamation of different processes coming together to form ...

Overcoming Diagnostic Delays in Pulmonary Hypertension With Deep-Learning ECG Analysis.

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is ...

Cross-Domain Transfer of EEG to EEG or ECG Learning for CNN Classification Models.

Electroencephalography (EEG) is often used to evaluate several types of neurological brain disorders...

Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone.

In this paper, a system to assess dyspnea with the mMRC scale, on the phone, via deep learning, is p...

A Deep Learning Architecture Using 3D Vectorcardiogram to Detect R-Peaks in ECG with Enhanced Precision.

Providing reliable detection of QRS complexes is key in automated analyses of electrocardiograms (EC...

3D ECG display with deep learning approach for identification of cardiac abnormalities from a variable number of leads.

The objective of this study is to explore new imaging techniques with the use of the deep learning m...

Accelerated Aging in LMNA Mutations Detected by Artificial Intelligence ECG-Derived Age.

OBJECTIVE: To demonstrate early aging in patients with lamin A/C (LMNA) gene mutations after hypothe...

Rams, hounds and white boxes: Investigating human-AI collaboration protocols in medical diagnosis.

In this paper, we study human-AI collaboration protocols, a design-oriented construct aimed at estab...

Hierarchical deep learning with Generative Adversarial Network for automatic cardiac diagnosis from ECG signals.

Cardiac disease is the leading cause of death in the US. Accurate heart disease detection is critica...

Generalized Generative Deep Learning Models for Biosignal Synthesis and Modality Transfer.

Generative Adversarial Networks (GANs) are a revolutionary innovation in machine learning that enabl...

Deep Learning of ECG for the Prediction of Postoperative Atrial Fibrillation.

A Tiny Matched Filter-Based CNN for Inter-Patient ECG Classification and Arrhythmia Detection at the Edge.

Automated electrocardiogram (ECG) classification using machine learning (ML) is extensively utilized...