Identifying alterations in the cardiac ventricles using radiomics with an ensemble multi-classifier approach.
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Updated
Jan 8, 2022 - Python
Identifying alterations in the cardiac ventricles using radiomics with an ensemble multi-classifier approach.
Special Project - CA classification (2019 Fall)
Atrial Fibrilation diagnosis based on the discriminative elements of an ensemble of GANs
A library for classifying single-lead ECG waveforms as either Normal Sinus Rhythm, Atrial Fibrillation, or Other Rhythm.
Code for the paper "Comparison of discrimination and calibration performance of ECG-based machine learning models for prediction of new-onset atrial fibrillation"
Software developed to carry out the End-of-Degree Project PRAFAI (Prediction of Recurrence of Atrial Fibrillation using Artificial Intelligence).
A Python implementation of a cellular automaton model of atrial fibrillation, an abnormal heart rhythm.
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
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
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".
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