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Epileptic seizure predictors based on computational intelligence techniques: A comparative study with 278 patients.

, , , , , , , , , and . Comput. Methods Programs Biomed., 114 (3): 324-336 (2014)

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Output regularization of SVM seizure predictors: Kalman Filter versus the "Firing Power" method., , , and . EMBC, page 6530-6533. IEEE, (2012)Robust and low complexity algorithms for seizure detection., , , , and . EMBC, page 4447-4450. IEEE, (2014)Optimal preictal period in seizure prediction., , , and . IWBBIO, page 1427-1433. Copicentro Editorial, (2014)Epileptic seizure prediction based on a bivariate spectral power methodology., , , and . EMBC, page 5943-5946. IEEE, (2012)Target Tracking Using Wavelet Features and RVM Classifier., , , and . ICNC (4), page 569-572. IEEE Computer Society, (2008)Wepilet, optimal orthogonal wavelets for epileptic seizure prediction with one single surface channel., , , and . EMBC, page 7059-7062. IEEE, (2011)Early Seizure Detection Using Neuronal Potential Similarity: A Generalized Low-Complexity and Robust Measure., , , , , and . Int. J. Neural Syst., 25 (5): 1550019:1-1550019:18 (2015)Epileptic Seizure Detection using Bipolar Singular Value Decomposition., , , and . BIOSIGNALS, page 178-183. SciTePress, (2015)Epileptic seizure predictors based on computational intelligence techniques: A comparative study with 278 patients., , , , , , , , , and . Comput. Methods Programs Biomed., 114 (3): 324-336 (2014)SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species., , , , , , , , , and 2 other author(s). PLoS Comput. Biol., (2019)