Incorporating structural information from the multichannel EEG improves patient-specific seizure detection
暂无分享,去创建一个
Wim Van Paesschen | Johan A. K. Suykens | Maarten De Vos | Borbála Hunyadi | Marco Signoretto | J. Suykens | S. Huffel | M. Signoretto | M. Vos | W. Paesschen | B. Hunyadi | Marco Signoretto
[1] Johan A. K. Suykens,et al. A kernel-based framework to tensorial data analysis , 2011, Neural Networks.
[2] Jeffrey M. Hausdorff,et al. Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .
[3] J. Gotman,et al. A patient-specific algorithm for the detection of seizure onset in long-term EEG monitoring: possible use as a warning device , 1997, IEEE Transactions on Biomedical Engineering.
[4] M. De Vos,et al. Automated artifact removal as preprocessing refines neonatal seizure detection , 2011, Clinical Neurophysiology.
[5] Johan A. K. Suykens,et al. Least Squares Support Vector Machine Classifiers , 1999, Neural Processing Letters.
[6] Malek Adjouadi,et al. Seizure Detection: An Assessment of Time- and Frequency-Based Features in a Unified Two-Dimensional Decisional Space Using Nonlinear Decision Functions , 2009, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[7] Andrew Zisserman,et al. Advances in Neural Information Processing Systems (NIPS) , 2007 .
[8] R B Reilly,et al. Classifier models and architectures for EEG-based neonatal seizure detection , 2008, Physiological measurement.
[9] Kazuyuki Aihara,et al. Classifying matrices with a spectral regularization , 2007, ICML '07.
[10] John M. Stern,et al. Atlas of EEG Patterns , 2004 .
[11] Sabine Van Huffel,et al. The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals , 2002, The European Symposium on Artificial Neural Networks.
[12] Johan A. K. Suykens,et al. Coupled Simulated Annealing , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[13] G. Lightbody,et al. EEG-based neonatal seizure detection with Support Vector Machines , 2011, Clinical Neurophysiology.
[14] S. Huffel,et al. Automated neonatal seizure detection mimicking a human observer reading EEG , 2008, Clinical Neurophysiology.
[15] Reza Tafreshi,et al. Automated Real-Time Epileptic Seizure Detection in Scalp EEG Recordings Using an Algorithm Based on Wavelet Packet Transform , 2010, IEEE Transactions on Biomedical Engineering.
[16] Konstantina S. Nikita,et al. Comparison of fractal dimension estimation algorithms for epileptic seizure onset detection , 2008, BIBE.
[17] Sabine Van Huffel,et al. Removal of Muscle Artifacts from EEG Recordings of Spoken Language Production , 2010, Neuroinformatics.
[18] Emmanuel J. Candès,et al. Exact Matrix Completion via Convex Optimization , 2009, Found. Comput. Math..
[19] J. Engel,et al. Surgery for seizures. , 1996, The New England journal of medicine.
[20] G. Lightbody,et al. A comparison of generative and discriminative approaches in automated neonatal seizure detection , 2009, 2009 IEEE International Symposium on Intelligent Signal Processing.
[21] Johan A. K. Suykens,et al. Least Squares Support Vector Machines , 2002 .
[22] Pramod P Khargonekar,et al. Support vector machines for seizure detection in an animal model of chronic epilepsy , 2010, Journal of neural engineering.
[23] A. Aertsen,et al. Detecting Epileptic Seizures in Long-term Human EEG: A New Approach to Automatic Online and Real-Time Detection and Classification of Polymorphic Seizure Patterns , 2008, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[24] R. Harner,et al. Patient-Specific Early Seizure Detection From Scalp Electroencephalogram , 2010, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.
[25] Johan A. K. Suykens,et al. LS-SVMlab Toolbox User's Guide , 2010 .
[26] Pablo A. Parrilo,et al. Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization , 2007, SIAM Rev..
[27] John Platt,et al. Probabilistic Outputs for Support vector Machines and Comparisons to Regularized Likelihood Methods , 1999 .
[28] Xuelong Li,et al. Supervised Tensor Learning , 2005, ICDM.
[29] Ali H. Shoeb,et al. Application of Machine Learning To Epileptic Seizure Detection , 2010, ICML.
[30] Wim Van Paesschen,et al. Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram , 2006, IEEE Transactions on Biomedical Engineering.
[31] Mark J. Cook,et al. Epileptic Seizures and the EEG: Measurement, Models, Detection and Prediction , 2010 .
[32] Deng Cai,et al. Tensor Subspace Analysis , 2005, NIPS.
[33] Josemir W Sander,et al. The global burden and stigma of epilepsy , 2008, Epilepsy & Behavior.
[34] J. Gotman,et al. A system to detect the onset of epileptic seizures in scalp EEG , 2005, Clinical Neurophysiology.
[35] Alexander J. Smola,et al. Advances in Large Margin Classifiers , 2000 .
[36] Marco Signoretto. Kernels and Tensors for Structured Data Modelling (Kernels en tensoren voor het modelleren van gestructureerde data) , 2011 .
[37] Patrick Dupont,et al. Canonical decomposition of ictal scalp EEG reliably detects the seizure onset zone , 2007, NeuroImage.
[38] Brian Litt,et al. One-Class Novelty Detection for Seizure Analysis from Intracranial EEG , 2006, J. Mach. Learn. Res..