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Automated detection and classification of high frequency oscillations (HFOs) in human intracereberal EEG., , , , and . Biomed. Signal Process. Control., 8 (6): 927-934 (2013)Epileptogenic zone localization based on partial directed coherence and graph analysis: a case study., , , , and . Signal Image Video Process., 17 (4): 955-963 (June 2023)Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS)., , , , , , , , , and 2 other author(s). Frontiers Neuroinformatics, (2017)Detection of High Frequency Oscillations (HFOs) in the 80-500 Hz range in epilepsy recordings using decision tree analysis., , , , and . IPAS, page 1-6. IEEE, (2014)Pitfalls of spikes filtering for detecting High Frequency Oscillations (HFOs)., , , , , and . SSD, page 427-432. IEEE, (2021)A comparative study between three epileptic high frequency oscillations detection strategies., , , , and . SSD, page 631-635. IEEE, (2020)Classification of epileptic cerebral activity using robust features and support vector machines., , , and . IPAS, page 1-6. IEEE, (2016)Interactive interface for spatio-temporal mapping of epileptic human brain using characteristics of high frequency oscillations (HFOs)., , , and . Biomed. Signal Process. Control., (August 2023)Detection of Epileptic High Frequency Oscillations Using Support Vector Machines., , , , , and . ATSIP, page 1-6. IEEE, (2020)Investigation of nonlinear granger causality in the context of epilepsy., , , , and . EUSIPCO, page 454-458. IEEE, (2017)