IEEE

Development and Validation of Feature-Based Machine Learning for ECG Artifact Detection and Classification

Abstract: ECG signals are vital for diagnosing cardiovascular diseases, but artifacts like power line interference, baseline wander, and motion artifacts hinder accurate interpretation. This study ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Scientific Research Publishing

Sporadic Hemiplegic Migraine Case Study and Classification Using Machine Learning ()

1 San Juan Bautista School of Medicine, Caguas, PR, USA. 2 Independent Researcher, Monmouth County, NJ, USA. There are two types of hemiplegic migraines: sporadic hemiplegic migraine (SHM) and ...
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 ...
Journal of Medical Internet Research

Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time ...

Classification models were developed using supervised machine learning algorithms (decision tree, support vector machines, k-nearest neighbor, and neural networks) and evaluated through ...
Healio

Q&A: Machine learning analysis of big data could transform how PCOS defined, managed

Please provide your email address to receive an email when new articles are posted on . Researchers are using machine learning to identify data-driven PCOS subtypes. Findings may lead to more precise ...
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 ...