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Machine learning detection of epileptic seizure onset zone from iEEG.
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Two-year experience of a newly established epilepsy monitoring unit in a resource-limited setting.
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High frequency oscillation network dynamics predict outcome in non-palliative epilepsy surgery.
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Interictal high-frequency oscillations generated by seizure onset and eloquent areas may be differentially coupled with different slow waves.
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Exploring the time-frequency content of high frequency oscillations for automated identification of seizure onset zone in epilepsy.
J Neural Eng. 2016 Apr;13(2):026026. doi: 10.1088/1741-2560/13/2/026026. Epub 2016 Feb 29.
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The morphology of high frequency oscillations (HFO) does not improve delineating the epileptogenic zone.
Clin Neurophysiol. 2016 Apr;127(4):2140-8. doi: 10.1016/j.clinph.2016.01.002. Epub 2016 Jan 21.
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Investigation of automatically detected high frequency oscillations (HFOs) as an early predictor of seizure onset zone.
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:6602-5. doi: 10.1109/EMBC.2015.7319906.
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The diagnostic utility of intracranial EEG monitoring for epilepsy surgery in children.
Epilepsia. 2015 Jul;56(7):1065-70. doi: 10.1111/epi.12983. Epub 2015 May 9.
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The spatial and signal characteristics of physiologic high frequency oscillations.
Epilepsia. 2014 Dec;55(12):1986-95. doi: 10.1111/epi.12851. Epub 2014 Dec 3.
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High frequency oscillations are associated with cognitive processing in human recognition memory.
Brain. 2014 Aug;137(Pt 8):2231-44. doi: 10.1093/brain/awu149. Epub 2014 Jun 11.
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Human intracranial high frequency oscillations (HFOs) detected by automatic time-frequency analysis.
PLoS One. 2014 Apr 10;9(4):e94381. doi: 10.1371/journal.pone.0094381. eCollection 2014.

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