Identifying alterations in the cardiac ventricles using radiomics with an ensemble multi-classifier approach.

Software developed to carry out the End-of-Degree Project PRAFAI (Prediction of Recurrence of Atrial Fibrillation using Artificial Intelligence).

Special Project - CA classification (2019 Fall)

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

A library for classifying single-lead ECG waveforms as either Normal Sinus Rhythm, Atrial Fibrillation, or Other Rhythm.

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

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

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

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

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

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

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".