AIMC Topic: Seizures

Clear Filters Showing 281 to 290 of 349 articles

Discriminating preictal and interictal brain states in intracranial EEG by sample entropy and extreme learning machine.

Journal of neuroscience methods
BACKGROUND: Epilepsy is one of the most common neurological disorders approximately one in every 100 people worldwide are suffering from it. Uncontrolled epilepsy poses a significant burden to society due to associated healthcare cost to treat and co...

On the proper selection of preictal period for seizure prediction.

Epilepsy & behavior : E&B
Supervised machine learning-based seizure prediction methods consider preictal period as an important prerequisite parameter during training. However, the exact length of the preictal state is unclear and varies from seizure to seizure. We propose a ...

Multifractal Analysis and Relevance Vector Machine-Based Automatic Seizure Detection in Intracranial EEG.

International journal of neural systems
Automatic seizure detection technology is of great significance for long-term electroencephalogram (EEG) monitoring of epilepsy patients. The aim of this work is to develop a seizure detection system with high accuracy. The proposed system was mainly...

Using trend templates in a neonatal seizure algorithm improves detection of short seizures in a foetal ovine model.

Physiological measurement
Seizures below one minute in duration are difficult to assess correctly using seizure detection algorithms. We aimed to improve neonatal detection algorithm performance for short seizures through the use of trend templates for seizure onset and end. ...

Kernel collaborative representation-based automatic seizure detection in intracranial EEG.

International journal of neural systems
Automatic seizure detection is of great significance in the monitoring and diagnosis of epilepsy. In this study, a novel method is proposed for automatic seizure detection in intracranial electroencephalogram (iEEG) recordings based on kernel collabo...

Comparative effectiveness of anti-seizure medications in emulated trials using medical informatics.

Brain : a journal of neurology
Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar sequence for many patients. Comparative effectiveness data beyond the first ASM prescription are limited. Artificial intelligence can automatically e...

CLaI: Collaborative Learning and Inference for Low-Resolution Physiological Signals: Validation in Clinical Event Detection and Prediction.

IEEE transactions on bio-medical engineering
While machine learning (ML) techniques have been applied to detection and prediction tasks in clinical data, most methods rely on high-resolution data, which is not routinely available in most Intensive Care Units (ICUs), and perform poorly when face...

Region-specific modulation and predictive potential of the oscillatory dynamics in an ex vivo model of ictogenesis in the CA1, CA3 and dentate gyrus.

Neuroscience letters
The hippocampus, including the cornu ammonis (CA) and dentate gyrus (DG) subregions, is a brain area highly susceptible to seizure-like activity (SLA). Most studies conducted in vivo have been performed in a single hippocampal subregion. In our study...

Association between long-term exposure of polystyrene microplastics and exacerbation of seizure symptoms: Evidence from multiple approaches.

Ecotoxicology and environmental safety
Microplastics are tiny plastic particles originating from both commercial product manufacturing and the degradation of larger plastic materials. These particles pose significant risks to environmental and animal health. A growing body of evidence hig...

Dynamic alterations of SEEG characteristics during peri-ictal period and localization of seizure onset zone.

Neurobiology of disease
BACKGROUND: The evolution in peri-ictal period (from pre-ictal to ictal phase) of seizures contains abundant epileptogenic information, which aids in exploring the mechanism of seizures and localizing the epileptogenic zone (EZ). This study aims to i...