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EKG Analysis code for the MI3 intern group at CHOC Children's

License: GNU General Public License v3.0

Python 87.70% Shell 2.32% R 9.99%
wavelet wavelets machine-learning ekg ecg medical-informatics data-science svm-model python ekg-analysis

ekg_analysis's Introduction

EKG Analysis

Who we are

The team on this project constitutes the the intern group at MI3 (Medical Intelligence and Innovation Institute) at the Children's Hospital of Orange County. We are a mixture of undergrad and grad students at Chapman University, studying pre-med, computer science, math, and data science to name a few.

Our Goal

We are participating in the PhysioNet 2017 Challenge: Atrial Fibrillation Classification from a Short Single Lead ECG Recording. By September 1st, 2017 we will have developed an effective model for classifying ECG (ECG and EKG are the same thing) signals into 4 categories:

  1. Normal
  2. AF (Atrial Fibrillation)
  3. Other (Arrhythmia)
  4. Noisy

The files you want to look at to understand the logic of our algorithm are wave.py and model.py

Check out our wiki for more information about usage, installation, contributing, code structure, etc.

ekg_analysis's People

Contributors

andylikescodes avatar samyachour avatar

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ekg_analysis's Issues

Help with running the code

Hi,
I was hoping if anyone can help me run the program. I have all the dependencies installed. But I am confused as to how to run it.

Thank You.

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