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".

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.

Atrial Fibrillation Detection Blood Pressure Monitor (Oscillometric Method)

Using deep learning to detect Atrial fibrillation

AF Classification from a short single lead ECG recording: the PhysioNet/Computing in Cardiology Challenge 2017

EKG Analysis code for the MI3 intern group at CHOC Children's

This repository contains code reproducing an existing method to detect atrial fibrillation using empirical mode decomposition of signals. This was a lecture that I gave for graduate-level BioSignal Processing course.

The code of An End-to-End Atrial Fibrillation Detection by A Novel Residual-Based Temporal Attention Convolutional Neural Network with Exponential Nonlinearity Loss

Segmentation of histological images and fibrosis identification with a convolutional neural network

Code for the paper "Comparison of discrimination and calibration performance of ECG-based machine learning models for prediction of new-onset atrial fibrillation"

A convolutional neural network to detect atrial fibrillation from a single-lead ECG

Atrial Fibrilation diagnosis based on the discriminative elements of an ensemble of GANs

Basic ontology to represent the article: "Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation"

Data Science Project - Time Series & Data Mining

Special Project - CA classification (2019 Fall)

Repository contains codes to run REACT mapping algorithm. REACT maps are a novel approach to identify organized islands in 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.

A Python implementation of a cellular automaton model of atrial fibrillation, an abnormal heart rhythm.

This system object can be used to detect Atrial Fibrillation in an ECG signal