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Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram

Code to reproduce results reported in our paper published as:

Truong, N. D., A. D. Nguyen, L. Kuhlmann, M. R. Bonyadi, J. Yang, S. Ippolito, and O. Kavehei (2018). "Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram." Neural Networks 105, 104-111. DOI:10.1016/j.neunet.2018.04.018.

Requirements

  • h5py (2.7.1)
  • hickle (2.1.0)
  • Keras (2.0.6)
  • matplotlib (1.3.1)
  • mne (0.11.0)
  • pandas (0.21.0)
  • scikit-learn (0.19.1)
  • scipy (1.0.0)
  • tensorflow-gpu (1.4.1)

How to run the code

  1. Set the paths in *.json files. Copy files in folder "copy-to-CHBMIT-folder" to your CHBMIT dataset folder.

  2. Run the code

python main.py --mode MODE --dataset DATASET
where:
  • MODE: cv, test
    • cv: leave-one-seizure-out cross-validation
    • test: ~1/3 of last seizures used for test, interictal signals are split accordingly
  • DATASET: FB, CHBMIT, Kaggle2014Pred