https://github.com/victorkifer/ecg-af-detection-physionet-2017

AF Classification from a short single lead ECG recording: the PhysioNet/Computing in Cardiology Challenge 2017
https://github.com/victorkifer/ecg-af-detection-physionet-2017

atrial-fibrillation ecg machine-learning physionet qrs-detection

Last synced: about 2 months ago
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AF Classification from a short single lead ECG recording: the PhysioNet/Computing in Cardiology Challenge 2017

• Host: GitHub
• URL: https://github.com/victorkifer/ecg-af-detection-physionet-2017
• Owner: victorkifer
• License: gpl-3.0
• Created: 2019-01-08T08:09:23.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2019-01-08T09:21:46.000Z (over 6 years ago)
• Last Synced: 2025-03-25T09:49:28.702Z (2 months ago)
• Topics: atrial-fibrillation, ecg, machine-learning, physionet, qrs-detection
• Language: Python
• Size: 30.1 MB
• Stars: 24
• Watchers: 1
• Forks: 6
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt
  • Authors: AUTHORS.txt

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README

        
# The challenge

PhysioNet Computing in Cardiology Challenge 2017: Atrial fibrillation detection from a short single lead ECG recording

https://physionet.org/challenge/2017/

The official results:

https://physionet.org/challenge/2017/results.csv

Our best result is 0.77.

# The team

University of Valencia: Computational Multiscale Simulation Lab (CoMMLab).

Team members:

- [Miguel Lozano](https://www.uv.es/mlozano/)

- Viktor Kifer

- [Francisco Martinez-Gil](https://www.uv.es/uvweb/universidad/es/ficha-persona-1285950309813.html?p2=fmgil)