Neonatal Seizure Detection Using Deep Convolutional Neural Networks

@article{Ansari2019NeonatalSD,
  title={Neonatal Seizure Detection Using Deep Convolutional Neural Networks},
  author={Amir H. Ansari and Perumpillichira J. Cherian and Alexander Caicedo and Gunnar Naulaers and Maarten De Vos and Sabine Van Huffel},
  journal={International journal of neural systems},
  year={2019},
  volume={29 4},
  pages={
          1850011
        }
}
Identifying a core set of features is one of the most important steps in the development of an automated seizure detector. In most of the published studies describing features and seizure classifiers, the features were hand-engineered, which may not be optimal. The main goal of the present paper is using deep convolutional neural networks (CNNs) and random forest to automatically optimize feature selection and classification. The input of the proposed classifier is raw multi-channel EEG and the… CONTINUE READING

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Dual deep neural network-based classifiers to detect experimental seizures

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