README.rst

auto-eeg-diagnosis-comparison

This repository contains resources that were used for our study entitled

"Machine-Learning-Based Diagnostics of EEG Pathology".

Requirements

The code in this repository uses

1. https://github.com/TNTLFreiburg/braindecode (0.4.7)
2. https://github.com/TNTLFreiburg/brainfeatures (0.0.3)
3. https://github.com/gemeinl/braindecode_lazy (commit c785237e03f6cb0d10a3d68690a6d7111b90e994)
4. https://github.com/alexandrebarachant/pyRiemann (0.2.5)
5. https://github.com/PatrykChrabaszcz/NeuralArchitectureSearch (commit 7ac028fba1a29c5fa5a96ca5d09e6e6f5ad732c8)

Data

Our study is based on the Temple University Hospital Abnormal EEG Corpus (v2.0.0) avilable for download at: https://www.isip.piconepress.com/projects/tuh_eeg/html/downloads.shtml

Citing

If you use this code in a scientific publication, please cite us as:

@article{gemein2020machine,
  title={Machine-Learning-Based Diagnostics of EEG Pathology},
  author={Gemein, Lukas AW and Schirrmeister, Robin T and Chrab{\k{a}}szcz, Patryk and Wilson, Daniel and Boedecker, Joschka and Schulze-Bonhage, Andreas and Hutter, Frank and Ball, Tonio},
  journal={NeuroImage},
  pages={117021},
  year={2020},
  publisher={Elsevier}
}