Results 131 to 140 of about 31,045 (212)

Intestinal microbiome alterations in pediatric epilepsy: Implications for seizures and therapeutic approaches

open access: yesEpilepsia Open, EarlyView.
Abstract The intestinal microbiome plays a pivotal role in maintaining host health through its involvement in gastrointestinal, immune, and central nervous system (CNS) functions. Recent evidence underscores the bidirectional communication between the microbiota, the gut, and the brain and the impact of this axis on neurological diseases, including ...
Teresa Ravizza   +4 more
wiley   +1 more source

A soft electrode array with reconfigurable hydrogel interfaces for high-fidelity neurophysiological monitoring during craniotomy. [PDF]

open access: yesProc Natl Acad Sci U S A
Yang G   +14 more
europepmc   +1 more source

Real world testing and cost‐effectiveness analysis of subcutaneous EEG (REAL‐ASE): Protocol for a prospective multicentre interventional trial

open access: yesEpilepsia Open, EarlyView.
Abstract Objective Epilepsy is a common condition associated with significant morbidity, mortality, and costs. Poor documentation of seizures is a major challenge in epilepsy care. Objective seizure counting with mobile devices may mitigate this challenge and improve patient management.
Matthew McWilliam   +8 more
wiley   +1 more source

Neonatal seizures: Advances in diagnosis and management

open access: yesEpilepsia Open, EarlyView.
Abstract The International League Against Epilepsy (ILAE) created the ILAE Neonatal Task Force that classified neonatal seizures, defined neonatal epilepsy syndromes, and specified treatment guidelines. These frameworks, in addition to improved access to genetic testing and other recent advances, have revolutionized the diagnosis and management of ...
Elissa G. Yozawitz   +2 more
wiley   +1 more source

AI‐based localization of the epileptogenic zone using intracranial EEG

open access: yesEpilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida   +5 more
wiley   +1 more source

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