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Name: Maxwell
Type: User
Company: RMIT
Bio: PhD in Electrical and Biomedical Engineering
Name: Maxwell
Type: User
Company: RMIT
Bio: PhD in Electrical and Biomedical Engineering
Algorithms for explaining machine learning models
Arrhythmia Classification through Characteristics Extraction with Discrete Wavelet Transform & WEKA/MATLAB Supervised Training
Biosignal Processing in Python
The purpose of this lab is to learn how to set up the wearable data acquisition system, collect the first sensor data, and filter and analyse the data.
The purpose of this lab is to introduce the student to the measurements and analysis of electrical activity from a 1 lead ECG to determine heart rate, heart rate variability, and energy expenditure.
The purpose of this unit is to introduce you to the measurement and analysis of electrical activity generated by skeletal muscle, including determining the magnitude of muscle activation, the frequency spectrum of the muscle activity, and the level of muscle fatigue.
Dicom ECG Viewer and Converter. Convert to PDF, PNG, JPG, SVG, ...
ECG arrhythmia classification using a 2-D convolutional neural network
Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database
ECG Classification, Continuous Wavelet Transform, CWT, Convolutional Neural Network, CNN, Arrhythmia, Heartbeat classification
Deep learning for 12-lead ECG interpretation
Code and Datasets for the paper "Interpretable deep learning for automatic diagnosis of 12-lead electrocardiogram", published on iScience in 2021.
A Matlab toolbox for cardiovascular signal processing
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 of the PTB-XL dataset
Public repository associated with "Deep Learning for ECG Analysis: Benchmarks and Insights from PTB-XL"
C# ECG Toolkit 2.5. Support for: SCP-ECG, DICOM, HL7 aECG, ISHNE & MUSE-XML. (Migrating from SourceForge ecgtoolkit-cs)
Python class for reading ECG XML files.
Turn your data frame into a tableau style drag and drop UI interface to build visualization in R.
InceptionTime: Finding AlexNet for Time Series Classification
Python implementation of k-Shape
EchoNet-LVH is a deep learning model that quantifies ventricular hypertrophy and predicts etiologies of increased wall thickness and LVH (amyloidosis, HCM, etc).
Python wrapper for BioPac's mpdev DLL to communicate with MP150 devices.
OSU Capstone Project 2020-21 - Natalie & Julian
Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020
Machine Learning project to predict heart diseases
Python ECG Toolkit
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.