Medical Xpress

AI model detects prediabetes using ECG data without need for blood tests

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been developed. This ...
Frontiers

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

ECG beat classification using XAI leverages advanced machine learning techniques to enhance transparency in automated diagnostic systems. Traditional classification methods often function as “black ...
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 ...
IEEE

ECGNet: High-Precision ECG Classification Using Deep Learning and Advanced Activation Functions

Abstract: The electrocardiogram (ECG) is an important tool in diagnosing heart diseases. In this study, we introduce ECGNet a customized deep learning model that utilizes advanced activation functions ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

Modeling Physical Activities, Behavioral Patterns, and Symptoms in Aging and Neurological Disorders via Novel Sensing and AI Techniques ...