Using deep learning to detect Atrial fibrillation
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Updated
Mar 7, 2019 - Jupyter Notebook
Using deep learning to detect Atrial fibrillation
Multi-label classfication of 8-leads ECGs.
Some simple experiments code of Biomedical.
A repository related to a master thesis in electronics, informatics and technology. Title: "Comparing Cardiological and Algorithm-Based ECG Interpretation in Athletes: Can Artificial Intelligence Improve the Algorithms?"
The repository contains the project https://github.com/mk590901/graph_widget: ported on Jetpack Compose the widget for visualization ECG.
Public repository associated with: "Using deep convolutional neural networks to predict patients age based on ECGs from an independent test cohort"
Diagnose mental stress by fusing single and continuous-cycle ECG
Maps the STAFF III Database of ECG data annotations file from one line per patient to one line per file
User interface for Withings integration written in Angular
Code for adaptive anomaly detection using transformer based Autoencoder in Federated setting
Non-Invasive point of care ECG signal detection and analytics for cardiac diseases
Classificação de séries temporais de sinais ECG com redes neurais convolucionais (CNN).
Python command line application used to denoise ECG data using wavelet transform, Savitky-Golay filter and Deep Neural Networks.
"A prototype for ECG monitoring using Arduino Uno and AD8232 sensor. This project includes real-time visualization of heart activity and customizable software for medical and educational purposes."
This system object can be used to detect Atrial Fibrillation in an ECG signal
ECG Classification usign Neural Networks
Course project for EE338 - Digital Signal Processing
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