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".

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.

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"

Data Science Project - Time Series & Data Mining

No description provided.

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

Generate a standardized 2D map of the left atrium by unfolding a 3D mesh and its variables

This repo contributes the usage of long term Atrial Fibrillation database to collect four types of cardiac arrhythmias data.

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

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

Classify the image of atrial fibrillation and normal sinus rhythm using mobile net

Special Project - CA classification (2019 Fall)

Atrial Fibrillation Detection System Using the CNN-BiLSTM Method Based on Shimmer Electrocardiography Sensor

Code and supporting files used as part of the impact evaluation of the Detect, Protect and Perfect (DPP) project to reduce stroke incidence by improving care of atrial fibrillation.

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

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

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 neighbors, multi-layer perceptron, focal loss, multi-scale decomposition, time-frequency analysis.

No description provided.

First guided project for the Scientific Computing Tools for Advanced Mathematical Modeling course of the MSc in Mathematical Engineering @ Polimi, A.Y. 2024-2025.

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

💔 Global and Local Prediction in Automatic detection of Atrial Fibrillation

Clinical usefulness of the SAMe-TT2R2 score to predict a poor TTR

Budget impact model for IXA-001 in resistant hypertension. Features population funnel analysis, uptake scenarios, secondary HTN etiology stratification, and interactive Streamlit dashboard with Excel exports.