Repository for the paper 'Prospects for AI-Enhanced ECG as a Unified Screening Tool for Cardiac and Non-Cardiac Conditions -- An Explorative Study in Emergency Care'.

Evaluation of electrophysiological signals

Cardiology hub written in Java 13, Thymeleaf and Bootstrap

BRAVEHEART: Open-source software for automated electrocardiographic and vectorcardiographic analysis

A python command line tool to read an SCP-ECG file and print structure information

R package for analysis of cardiovascular research data

The ECG Detection with Deep Learning project employs Convolutional Neural Networks to automatically analyze Electrocardiogram (ECG) data, facilitating precise detection of cardiac abnormalities and enhancing diagnostic accuracy.

[CHIL 2024] Interpretation of Intracardiac Electrograms Through Textual Representations

Motion Analysis of Ring-Shaped tissues - code from Seguret et al. 2024 eLife

a small python Library for calculating cardiovascular diseases risk using different clinically validated algorithms

An advanced ECG anomaly detection system using deep learning. This repository contains a CNN autoencoder trained on the PTBDB dataset to identify abnormal heart rhythms. It employs various loss functions for model optimization and provides comprehensive visualizations of the results.

A promotional site for Dr. Julie Freed's research laboratory. Built with Gatsby.

HAMDARDDIALYSIS is a renowned healthcare facility specializing in nephrology, dialysis, and various medical treatments. Our expert nephrologists and cutting-edge dialysis unit provide exceptional care. We also offer comprehensive medical treatments onsite and have dedicated ambulance services for emergencies. With a patient-centered approach, we p

Multimodal Transformer Networks with synchronised ECG and PCG data to detect and classify Cardiovascular Diseases

This is a cardio tracker app for tracking heart rate, systolic pressure & diastolic pressure

Code for paper "Deciphering simultaneous heart conditions with spectrogram and explainable-AI approach".

Detecting elevated hemodynamics from the 12-lead ECG alone

Code for creating graphs and statistical investigations

ECG classification using MIT-BIH data, a deep CNN learning implementation of Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network, https://www.nature.com/articles/s41591-018-0268-3 and also deploy the trained model to a web app using Flask, introduced at

Heart Disease Prediction Using Machine Learning