Latest AI and machine learning research in myocardial infarction for healthcare professionals.
In this paper, we propose a lightweight neural network for real-time electrocardiogram (ECG) anomaly...
Atrial fibrillation (AF) is the most common type of sustained arrhythmia. It results from abnormal i...
Diagnosing COVID-19 accurately and rapidly is vital to control its quick spread, lessen lockdown res...
BACKGROUND: Congenital long QT syndrome (LQTS) is a rare heart disease caused by various underlying ...
The existing electrocardiogram (ECG) biometrics do not perform well when ECG changes after the enrol...
In the field of medical informatics, sleep staging is a challenging and time consuming task undertak...
Myocardial infarction (MI) accounts for a high number of deaths globally. In acute MI, accurate elec...
Modality translation grants diagnostic value to wearable devices by translating signals collected fr...
The objective of this work is to develop a fusion artificial intelligence (AI) model that combines p...
Heart disease is one of the significant challenges in today's world and one of the leading causes of...
Electrocardiogram signal (ECG) is considered a significant biological signal employed to diagnose he...
BACKGROUND AND OBJECTIVE: The automatic recognition of myocardial infarction (MI) by artificial inte...
This study is aimed at analyzing the important role of deep learning-based electrocardiograph (ECG) ...
Premature ventricular contraction (PVC) is one of the common ventricular arrhythmias, which may caus...
Millions of people around the world are affected by arrhythmias, which are abnormal activities of th...
PURPOSE: Surface electromyography (sEMG) is vulnerable to environmental interference, low recognitio...
Physicians manually interpret an electrocardiogram (ECG) signal morphology in routine clinical pract...
Electrocardiographic imaging (ECGi) reconstructs electrograms at the heart's surface using the poten...
INTRODUCTION: Robotics in percutaneous coronary intervention (R-PCI) has been one such area of advan...
In the past decade, deep learning models have been applied to bio-sensors used in a body sensor netw...
The biometric identification method is a current research hotspot in the pattern recognition field. ...