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.
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:
- Normal
- AF (Atrial Fibrillation)
- Other (Arrhythmia)
- 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.