How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
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A rule-based seizure prediction method for focal neocortical epilepsySeizure prediction in hippocampal and neocortical epilepsy using a model-based approach.Ngram-derived pattern recognition for the detection and prediction of epileptic seizures.Scale invariance properties of intracerebral EEG improve seizure prediction in mesial temporal lobe epilepsy.Measuring predictability of autonomous network transitions into bursting dynamicsA fuzzy logic system for seizure onset detection in intracranial EEGA stochastic framework for evaluating seizure prediction algorithms using hidden Markov models.Slow modulations of high-frequency activity (40-140-Hz) discriminate preictal changes in human focal epilepsy.Seizure prediction.Role of multiple-scale modeling of epilepsy in seizure forecasting.A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction.Fast monitoring of epileptic seizures using recurrence time statistics of electroencephalography.Complexity measures of brain wave dynamics.Patient specific seizure prediction system using Hilbert spectrum and Bayesian networks classifiers.Space-time adaptive processing for improved estimation of preictal seizure activity.Localizing epileptic seizure onsets with Granger causality.Enhanced phase and amplitude synchronization toward focal seizure offset.Detecting dynamical changes in time series using the permutation entropy.Is Using Threshold-Crossing Method and Single Type of Features Sufficient to Achieve Realistic Application of Seizure Prediction?Deterministic dynamics of neural activity during absence seizures in rats.Testing statistical significance of multivariate time series analysis techniques for epileptic seizure prediction.Seizure anticipation: do mathematical measures correlate with video-EEG evaluation?Seizure prediction with spectral power of EEG using cost-sensitive support vector machines.Seizure prediction in patients with focal hippocampal epilepsy.Functional isolation within the cerebral cortex in the vegetative state: a nonlinear method to predict clinical outcomes.Classification of epilepsy using high-order spectra features and principle component analysis.Automatic identification of epileptic and background EEG signals using frequency domain parameters.Correlation dimension and integral do not predict epileptic seizures.
P2860
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P2860
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
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2003 nî lūn-bûn
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2003年の論文
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How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
@en
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
@nl
type
label
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
@en
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
@nl
prefLabel
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
@en
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
@nl
P2093
P356
P1433
P1476
How well can epileptic seizures be predicted? An evaluation of a nonlinear method.
@en
P2093
Aschenbrenner-Scheibe R
Schulze-Bonhage A
Winterhalder M
P304
P356
10.1093/BRAIN/AWG265
P407
P577
2003-09-23T00:00:00Z