AIMC Topic: Epilepsy

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Digital conversations about suicide among teenagers and adults with epilepsy: A big-data, machine learning analysis.

Epilepsia
OBJECTIVE: Digital media conversations can provide important insight into the concerns and struggles of people with epilepsy (PWE) outside of formal clinical settings and help generate useful information for treatment planning. Our study aimed to exp...

Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning.

Computational and mathematical methods in medicine
Electroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy. Clinically reading tens or even hundreds of hours of EEG recordings is very time consum...

An artificial intelligence-based EEG algorithm for detection of epileptiform EEG discharges: Validation against the diagnostic gold standard.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To validate an artificial intelligence-based computer algorithm for detection of epileptiform EEG discharges (EDs) and subsequent identification of patients with epilepsy.

A propositional AI system for supporting epilepsy diagnosis based on the 2017 epilepsy classification: Illustrated by Dravet syndrome.

Epilepsy & behavior : E&B
PURPOSE: The 2017 epilepsy and seizure diagnosis framework emphasizes epilepsy syndromes and the etiology-based approach. We developed a propositional artificial intelligence (AI) system based on the above concepts to support physicians in the diagno...

SeizureBank: A Repository of Analysis-ready Seizure Signal Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Approximately 60 million people worldwide suffer from epileptic seizures. A key challenge in machine learning ap proaches for epilepsy research is the lack of a data resource of analysis-ready (no additional preprocessing is needed when using the dat...

Novel Deep Learning Network Analysis of Electrical Stimulation Mapping-Driven Diffusion MRI Tractography to Improve Preoperative Evaluation of Pediatric Epilepsy.

IEEE transactions on bio-medical engineering
OBJECTIVE: To investigate the clinical utility of deep convolutional neural network (DCNN) tract classification as a new imaging tool in the preoperative evaluation of children with focal epilepsy (FE).

Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing.

Artificial intelligence in medicine
BACKGROUND AND OBJECTIVE: Multimodal data analysis and large-scale computational capability is entering medicine in an accelerative fashion and has begun to influence investigational work in a variety of disciplines. It is also informing us of therap...

QuPWM: Feature Extraction Method for Epileptic Spike Classification.

IEEE journal of biomedical and health informatics
Epilepsy is a neurological disorder ranked as the second most serious neurological disease known to humanity, after stroke. Inter-ictal spiking is an abnormal neuronal discharge after an epileptic seizure. This abnormal activity can originate from on...