Open-source device for measuring cardiograpgy signals with a GUI for easier handling and additional software for analyzing the data.
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Updated
Jul 22, 2025 - Jupyter Notebook
Open-source device for measuring cardiograpgy signals with a GUI for easier handling and additional software for analyzing the data.
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
ECG classification from short single lead segments (Computing in Cardiology Challenge 2017 entry)
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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'.
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Cardiovascular Activity Monitoring Using mmWaves
[ NeurIPS 2022 ] Official Codebase for "ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography"
Portable WiFi Connected IoT ECG Monitor 📈💕
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[CHIL 2024] Interpretation of Intracardiac Electrograms Through Textual Representations
алгоритм, занявший второе место на конкурсе http://cardioqvark.ru/challenge/
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AI based detection and classification of Anomalous Aortic Origin of Coronary Arteries in Coronary CT Angiography
Solving physionet2017 with RCRNN
Cardioinformatics: the nexus of bioinformatics and precision cardiology
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.
Pulse oximetry data processing and classification
Python package for preprocessing OpenSlide image files and their corresponding annotations for use with Machine Learning segmentation models.
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