Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures

@article{Golmohammadi2019AutomaticAO,
  title={Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures},
  author={Meysam Golmohammadi and Amir Hossein Harati Nejad Torbati and Silvia Lopez de Diego and Iyad Obeid and Joseph W. Picone},
  journal={Frontiers in Human Neuroscience},
  year={2019},
  volume={13}
}
Brain monitoring combined with automatic analysis of EEGs provides a clinical decision support tool that can reduce time to diagnosis and assist clinicians in real-time monitoring applications (e.g., neurological intensive care units). Clinicians have indicated that a sensitivity of 95% with specificity below 5% was the minimum requirement for clinical acceptance. In this study, a high-performance automated EEG analysis system based on principles of machine learning and big data is proposed… 

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