Automated Seizure Detection and Seizure Type Classification From Electroencephalography With a Graph Neural Network and Self-Supervised Pre-Training.
Siyi TangJared A. DunnmonKhaled SaabXuan ZhangQianying HuangFlorian DubostDaniel L. RubinChristopher Lee-MesserPublished in: CoRR (2021)
Keyphrases
- eeg signals
- eeg data
- neural network
- epileptic seizures
- multi layer perceptron
- training process
- training set
- brain computer interface
- independent component analysis
- pattern recognition
- signal processing
- training samples
- training phase
- video recordings
- training patterns
- learning vector quantization
- brain activity
- feed forward neural networks
- automated classification
- artificial neural networks
- train a neural network
- machine learning
- neural network model
- supervised learning
- automated analysis
- training algorithm
- detection algorithm
- pattern classification
- support vector
- feedforward neural networks
- incremental learning
- classification method
- graph structure
- object detection
- decision trees
- digital mammograms
- neural network training
- knn
- discriminative classifiers
- text classification
- false positives
- detection method
- self organizing maps
- feature vectors
- random walk
- feature space
- nearest neighbour
- selected features