AIMC Topic: Epilepsy

Clear Filters Showing 291 to 300 of 424 articles

Patient-Specific Seizure Detection Method using Hybrid Classifier with Optimized Electrodes.

Journal of medical systems
In this paper the EEG signal is analyzed by reconstructing the time series EEG signal in High dimensional Phase Space. The computational complexity in higher dimension is reduced by Principal Component Analysis for the High dimensional Phase Space ou...

Automatic diagnosis of neurological diseases using MEG signals with a deep neural network.

Scientific reports
The application of deep learning to neuroimaging big data will help develop computer-aided diagnosis of neurological diseases. Pattern recognition using deep learning can extract features of neuroimaging signals unique to various neurological disease...

Alternative Diagnosis of Epilepsy in Children Without Epileptiform Discharges Using Deep Convolutional Neural Networks.

International journal of neural systems
Numerous nonepileptic paroxysmal events, such as syncope and psychogenic nonepileptic seizures, may imitate seizures and impede diagnosis. Misdiagnosis can lead to mistreatment, affecting patients' lives considerably. Electroencephalography is common...

UHPLC-MS/MS method for simultaneous determination of carbamazepine and its seven major metabolites in serum of epileptic patients.

Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Carbamazepine (CBZ) was considered as the drug of choice in the treatment for various forms of epilepsy, yet the non-negligible adverse effects of CBZ suspend as the major concern for rational and efficient clinical medication. This study developed a...

Automatic seizure detection using three-dimensional CNN based on multi-channel EEG.

BMC medical informatics and decision making
BACKGROUND: Automated seizure detection from clinical EEG data can reduce the diagnosis time and facilitate targeting treatment for epileptic patients. However, current detection approaches mainly rely on limited features manually designed by domain ...

Prediction error connectivity: A new method for EEG state analysis.

NeuroImage
Several models have been proposed to explain brain regional and interregional communication, the majority of them using methods that tap the frequency domain, like spectral coherence. Considering brain interareal communication as binary interactions,...

Identification of Hidden Sources by Estimating Instantaneous Causality in High-Dimensional Biomedical Time Series.

International journal of neural systems
The study of connectivity patterns of a system's variables, such as multi-channel electroencephalograms (EEG), is of utmost importance towards a better understanding of its internal evolutionary mechanisms. Here, the problem of estimating the connect...

Therapeutic drug monitoring of levetiracetam in daily clinical practice: high-performance liquid chromatography versus immunoassay.

European journal of hospital pharmacy : science and practice
OBJECTIVES: Although levetiracetam presents an easy dosing and tolerability, therapeutic drug monitoring may be recommended in certain situations. Measurement of levetiracetam in serum plasma is commonly done by high performance liquid chromatography...

Seizure forecasting using single robust linear feature as correlation vector of seizure-like events in brain slices preparation in vitro.

Neurological research
Epilepsy is a neurological disorder affecting 50 million individuals globally. Modern research has inspected the likelihood of forecasting epileptic seizures. Algorithmic investigations are giving promising results for seizure prediction. Though most...

Automated seizure prediction.

Epilepsy & behavior : E&B
In the past two decades, significant advances have been made on automated electroencephalogram (EEG)-based diagnosis of epilepsy and seizure detection. A number of innovative algorithms have been introduced that can aid in epilepsy diagnosis with a h...