Results 51 to 60 of about 36,558 (266)
Epileptic Disorders, EarlyView.Abstract Objective Febrile seizures (FS) are the most common seizures in childhood, yet identifying children at risk of developing epilepsy after the first FS remains challenging. We aimed to evaluate the prognostic potential of machine learning (ML) algorithms applied to post‐febrile seizure electroencephalography (EEG) recordings.
Boran Şekeroğlu +7 more
wiley +1 more source
Epilepsia, EarlyView.Abstract Objective Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a commonly prescribed first‐line ASM, yet only approximately half of patients achieve sustained seizure freedom. Treatment selection remains largely empirical.
Simeon Platte +15 more
wiley +1 more source
Ultrafast oscillations in the human brain and their functional significance
Epilepsia, EarlyView.Abstract Objective The upper frequency limit of human brain activity remains unknown. Using ultrahigh sampling rate (≥20 kHz) intracranial microelectroencephalography, this study aimed to systematically explore and quantitatively characterize brain field oscillations beyond the established high‐frequency oscillation range (>2 kHz), and to determine ...
Milan Brázdil +13 more
wiley +1 more source
The Crest factor for trigonometric polynomials. Part I: Approximation theoretical estimates
Journal of Numerical Analysis and Approximation Theory, 2001 The Chebyshev norm of a degree n trigonometric polynomial is estimated against a discrete maximum norm based on equidistant sampling points where, typically, oversampling rather than critical sampling is used. The bounds are derived from various methods
K. Jetter, G. Pfander, G. Zimmermann
doaj +2 more sources
Hippocampal network activity changes during early epileptogenesis predict subsequent epilepsy
Epilepsia, EarlyView.Abstract Objective Despite decades of research, the circuit mechanisms that underlie focal epileptogenesis remain incompletely understood. In this study, we aimed to characterize the changes in hippocampal network activity induced by an epileptogenic insult.
Michael Strüber +13 more
wiley +1 more source
Decision Support Model for Time Series Data Augmentation Method Selection
IEEE AccessData augmentation (DA) plays a crucial role in machine learning by improving model generalization and tackling data scarcity issues, particularly prevalent in domains with limited access to sensitive information or rare events.
Dorian Joubaud +4 more
doaj +1 more source
Epilepsia, EarlyView.Abstract Objective Despite elevated risk for epilepsy following traumatic brain injury (TBI), there are limited tools to assess epilepsy risk following TBI using routine clinical data. The objective of this study was to develop and validate a machine learning approach to predict the onset of posttraumatic epilepsy (PTE) over varying time horizons ...
Mustafa Ozmen +6 more
wiley +1 more source
PLoS ONE, 2020 One of the fundamental challenges when dealing with medical imaging datasets is class imbalance. Class imbalance happens where an instance in the class of interest is relatively low, when compared to the rest of the data.
Kevin Teh +4 more
doaj +1 more source
JCPP Advances, EarlyView.Abstract Background Facets of decision‐making and risk‐taking are implicated in adolescent health risk behaviors; however, whether they may lead to adolescent engagement in substance use, gambling, and self‐harm is unknown. Methods We used the Millennium Cohort Study to test whether a task‐based measure of decision‐making and risk‐taking predicts ...
Nicole G. Hammond +4 more
wiley +1 more source
, 2010 Publication in the conference proceedings of EUSIPCO, Aalborg, Denmark ...
Weiss, Stephan +3 more
openaire +4 more sources