Frontiers

Advances in machine and deep learning for ECG beat classification: a systematic review

The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...
IEEE

An ECG Data Feature Selection Comparison: Machine Learning and Expert Doctors

The ECG signals analysis is a frequently used approach for classification of cardiac patients. Traditionally, this analysis is made by expert doctors. However, recently, it is increasingly supported ...
ahajournals.org

Abstract 4368538: Fusion Machine Learning Architectures for Improving ECG classification of acute coronary events

Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
Frontiers

Advanced ECG feature extraction and SVM classification for predicting defibrillation success in OHCA

Out-of-hospital cardiac arrest (OHCA) represents a critical challenge for emergency medical services, with the necessity for rapid and accurate prediction of defibrillation outcomes to enhance patient ...
IEEE

FSHOADC - Feature Selection and Hyperparameter Optimization Based Arrhythmia Detection and Classification: A Machine Learning Approach for Arrhythmia Detection using ECG Signals

Abstract: One essential and often used tool for the diagnosis of cardiovascular disorders is the electrocardiogram (ECG). With the emergence of artificial intelligence (AI), it is possible to have ...