ahajournals.org

Abstract 4366733: Deep Learning-Based BNP Classification from Single-Lead ECG

Background: Brain natriuretic peptide (BNP) is a key heart failure biomarker. Single-lead electrocardiograms (ECGs) from wearable devices offer valuable diagnostic and prognostic insights. We ...
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 ...
IEEE

Detection of Bundle Branch Block From 12-Lead ECG Using Fifth-Order Tensor-Domain Machine Learning

Abstract: Bundle branch block (BBB) is a cardiac disease that occurs due to the delay in the heart’s electrical activity during a heartbeat. The early detection of BBB using 12-lead electrocardiogram ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
EDN

DIY EKG Using Arduino and Javascript

An electrocardiogram or EKG is a testing equipment used to measure the electrical activity of the heart. Using only an Arduino Shield and a set of electrodes, one can create his own EKG, generate a ...