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The present study verified that lncRNA NEAT1 affected inflammatory response of epilepsy by suppressing miR-129-5p and further regulating Notch signaling pathway in IL-1β-induced epilepsy cell model.
This could result from either an effect of LGI1 on risk for generalized epilepsy or an effect of co-occurring idiopathic generalized epilepsy-specific genes in these families.

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Epilepsy detection from ecg?5 answersEpilepsy detection from EEG signals is a challenging task due to the labor-intensive nature of the procedure, lack of trained professionals, and inherent variability in the EEG of different patients. However, several studies have proposed automatic seizure detection systems using machine learning techniques. These systems analyze and detect seizures in single-channel EEG from multiple patients by classifying EEG instances as seizure or non-seizure based on learned features from the training set. Features extracted from the time, frequency, and time-frequency domains are combined to capture information about EEG signals' amplitude, frequency, and morphology. Experimental work has been conducted to establish the best algorithms and parameters for preprocessing, feature selection, and classification. The proposed systems have achieved high accuracy, specificity, and sensitivity, exceeding 99% and 98.9% respectively. Additionally, the use of Discrete Wavelet Transform (DWT) and machine learning classifiers has shown promising results in epilepsy detection, achieving maximum accuracy, sensitivity, specificity, precision, and recall of 100%.
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What is the role of AI in epilepsy?5 answersArtificial intelligence (AI) has been applied to neuroimaging in patients with epilepsy to enhance classification of clinical diagnosis, prediction of treatment outcomes, and the understanding of cognitive comorbidities. AI-based tools have been used to develop a novel data-driven disease taxonomy based on distinct patterns of brain atrophy in epilepsy patients, which could be used for individualized prognostics and targeted therapeutics. Additionally, a propositional AI system has been developed to support physicians in the diagnosis of epilepsy by analyzing and building ontology knowledge for the classification of seizure patterns, epilepsy syndromes, and etiologies. The use of AI in epilepsy research has the potential to improve diagnosis, prognosis, and treatment outcomes for patients with epilepsy.
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