Repository contains codes to run REACT mapping algorithm. REACT maps are a novel approach to identify organized islands in atrial fibrillation.
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Updated
Jun 20, 2024
Repository contains codes to run REACT mapping algorithm. REACT maps are a novel approach to identify organized islands in atrial fibrillation.
Feng et al. Front Cardiovasc Med. 2023 Oct 2;10:1189293. doi: 10.3389/fcvm.2023.1189293. eCollection 2023.
Code for the paper "Comparison of discrimination and calibration performance of ECG-based machine learning models for prediction of new-onset atrial fibrillation"
Data Science Project - Time Series & Data Mining
Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".
A Python implementation of a cellular automaton model of atrial fibrillation, an abnormal heart rhythm.
Software developed to carry out the End-of-Degree Project PRAFAI (Prediction of Recurrence of Atrial Fibrillation using Artificial Intelligence).
Identifying alterations in the cardiac ventricles using radiomics with an ensemble multi-classifier approach.
Using deep learning to detect Atrial fibrillation
Atrial Fibrillation Detection Blood Pressure Monitor (Oscillometric Method)
This is a CNN based model which aims to automatically classify the ECG signals of a normal patient vs. a patient with AF and has been trained to achieve up to 93.33% validation accuracy.
In this study we will introduce atrial fibrillation, one of the cardiac arrhythmias, and see how it can be diagnosed using convolutional neural networks in combination with various methods and supervised learning models, including: gray-level co-occurrence matrix, short-time Fourier transform based spectrogram, support-vector machines, k-nearest…
Atrial Fibrilation diagnosis based on the discriminative elements of an ensemble of GANs
Special Project - CA classification (2019 Fall)
The code of An End-to-End Atrial Fibrillation Detection by A Novel Residual-Based Temporal Attention Convolutional Neural Network with Exponential Nonlinearity Loss
This system object can be used to detect Atrial Fibrillation in an ECG signal
Basic ontology to represent the article: "Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation"
Takes data from the atrial fibrillation database from Physionet, and attempts to detect that atrial fibrillation using a number of statistical methods. Matlab code.
💔 Global and Local Prediction in Automatic detection of Atrial Fibrillation
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