🐍 Semi-automated batch seizure detection using deep learning.

-> Check out the online version ⚡ developed by @matteocargnelutti.

1. Download and install miniconda on your platform

2. Clone or Download deep-seizure-detect

3. Start Anaconda's shell prompt, navigate to /deep-seizure-detect:

    # create conda environment with python version 3.7.7
    conda create --name myenv python=3.7.7     
    
    # enter conda environment
    conda activate myenv
    
    # install dependencies
    conda install -c anaconda keras
    conda install -c anaconda scikit-learn
    conda install -c anaconda matplotlib
    conda install -c anaconda seaborn
    conda install -c anaconda numba
    conda install -c anaconda tqdm
    pip install tables
    pip install pick
    
    # optional for gpu usage
    conda install tensorflow-gpu
   

Start Anaconda's shell prompt

    # navigate to *deep-seizure-detect* folder
    cd ./deep-seizure-detect

    # enter conda environment
    conda activate myenv

    # Get path of the folder containing reorganized_data subfolder with data to generate predictions       
    python get_path.py
    
    # generate predictions
    python batch_predict.py
    
    # verify seizures
    python app.py

For configuration settings and file preparation check this guide -> configuration

The model is a convolutional neural net that was built using Keras API with a Tensorflow-backend. It was trained on LFP data from chronically epileptic mice that were generated using intra-hippocampal kainate injections by Dr. Trina Basu.

deep-seizure-detect was developed by Pantelis Antonoudiou. This open-source software is distributed under the Apache 2.0 License.