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Epilepsy

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Characterizing Brain Signals for Epileptic Pre-ictal Signal Classification.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Epilepsy is a kind of neurological disorder characterized by recurrent epileptic seizures. While it is crucial to characterize pre-ictal brain electrical activities, the problem to this day still remains computationally challenging. Using brain signa...

Epileptic Seizure Detection with Hybrid Time-Frequency EEG Input: A Deep Learning Approach.

Computational and mathematical methods in medicine
The precise detection of epileptic seizure helps to prevent the serious consequences of seizures. As the electroencephalogram (EEG) reflects the brain activity of patients effectively, it has been widely used in epileptic seizure detection in the pas...

A simulation study to investigate the use of concentric tube robots for epilepsy surgery.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
PURPOSE: Patients with pharmacoresistant refractory epilepsy may require epilepsy surgery to prevent future seizure occurrences. Conventional surgery consists of a large craniotomy with straight rigid tools with associated outcomes of morbidity, larg...

Ontology-based identification and prioritization of candidate drugs for epilepsy from literature.

Journal of biomedical semantics
BACKGROUND: Drug repurposing can improve the return of investment as it finds new uses for existing drugs. Literature-based analyses exploit factual knowledge on drugs and diseases, e.g. from databases, and combine it with information from scholarly ...

Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches.

Computational and mathematical methods in medicine
Epileptic seizures occur due to brain abnormalities that can indirectly affect patient's health. It occurs abruptly without any symptoms and thus increases the mortality rate of humans. Almost 1% of world's population suffers from epileptic seizures....

Artificial intelligence for medical image analysis in epilepsy.

Epilepsy research
Given improvements in computing power, artificial intelligence (AI) with deep learning has emerged as the state-of-the art method for the analysis of medical imaging data and will increasingly be used in the clinical setting. Recent work in epilepsy ...

Fine motor impairment in children with epilepsy: Relations with seizure severity and lateralizing value.

Epilepsy & behavior : E&B
Motor skill deficits are common in epilepsy. The Grooved Pegboard Test (GPT) is the most commonly used fine motor task and is included in the NIH Common Data Elements Battery for the assessment of epilepsy. However, there are limited data on its util...

Dynamic training of a novelty classifier algorithm for real-time detection of early seizure onset.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To develop an adaptive framework for seizure detection in real-time that is practical to use in the Epilepsy Monitoring Unit (EMU) as a warning signal, and whose output helps characterize epileptiform activity.

DNA methylation-based classification of malformations of cortical development in the human brain.

Acta neuropathologica
Malformations of cortical development (MCD) comprise a broad spectrum of structural brain lesions frequently associated with epilepsy. Disease definition and diagnosis remain challenging and are often prone to arbitrary judgment. Molecular classifica...

Epileptic Seizures Detection in EEG Signals Using Fusion Handcrafted and Deep Learning Features.

Sensors (Basel, Switzerland)
Epilepsy is a brain disorder disease that affects people's quality of life. Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper provides a computer-aided diagnosis system (CADS) for the automatic diagnosis of epil...