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Permutation Entropy-Based Interpretability of Convolutional Neural Network Models for Interictal EEG Discrimination of Subjects with Epileptic Seizures vs. Psychogenic Non-Epileptic Seizures.

, , , , , , , , and . Entropy, 24 (1): 102 (2022)

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Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia., , , , , , , , , and 7 other author(s). Int. J. Neural Syst., 27 (2): 1650039:1-1650039:15 (2017)Information Theoretic-Based Interpretation of a Deep Neural Network Approach in Diagnosing Psychogenic Non-Epileptic Seizures., , , , , , , , and . Entropy, 20 (2): 43 (2018)A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects., , , , , , , , and . Sensors, 20 (4): 1235 (2020)Permutation Entropy-Based Interpretability of Convolutional Neural Network Models for Interictal EEG Discrimination of Subjects with Epileptic Seizures vs. Psychogenic Non-Epileptic Seizures., , , , , , , , and . Entropy, 24 (1): 102 (2022)Usage of network analysis to investigate Periodic Sharp Wave Complexes in EEGs of patients with sporadic CJD., , , , , , , and . SEBD, volume 2037 of CEUR Workshop Proceedings, page 1. CEUR-WS.org, (2017)A network analysis based approach to characterizing periodic sharp wave complexes in electroencephalograms of patients with sporadic CJD., , , , , , , and . Int. J. Medical Informatics, (2019)