AI Medical Compendium Journal:
Epilepsy & behavior : E&B

Showing 31 to 34 of 34 articles

Machine learning as a new paradigm for characterizing localization and lateralization of neuropsychological test data in temporal lobe epilepsy.

Epilepsy & behavior : E&B
In this study, we employed a kernel support vector machine to predict epilepsy localization and lateralization for patients with a diagnosis of epilepsy (n = 228). We assessed the accuracy to which indices of verbal memory, visual memory, verbal flue...

Validation of a novel classification model of psychogenic nonepileptic seizures by video-EEG analysis and a machine learning approach.

Epilepsy & behavior : E&B
The aim of this study was to validate a novel classification for the diagnosis of PNESs. Fifty-five PNES video-EEG recordings were retrospectively analyzed by four epileptologists and one psychiatrist in a blind manner and classified into four distin...

Cortical feature analysis and machine learning improves detection of "MRI-negative" focal cortical dysplasia.

Epilepsy & behavior : E&B
Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common lesion in adults with treatment-resistant epilepsy. Advances in MRI have revolutionized the diagnosis of FCD, resulting in higher success rates fo...

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 ...