Neurology

Seizures

Latest AI and machine learning research in seizures for healthcare professionals.

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Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The E...

Sep 2017 28974302
Detection of Interictal Discharges With Convolutional Neural Networks Using Discrete Ordered Multichannel Intracranial EEG.

Detection algorithms for electroencephalography (EEG) data, especially in the field of interictal ep...

Sep 2017 28952945
Fusion of Facial Expressions and EEG for Multimodal Emotion Recognition.

This paper proposes two multimodal fusion methods between brain and peripheral signals for emotion r...

Sep 2017 29056963
A Functional-Genetic Scheme for Seizure Forecasting in Canine Epilepsy.

OBJECTIVE: The objective of this work is the development of an accurate seizure forecasting algorith...

Sep 2017 28920893
Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning.

Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiologic...

Sep 2017 28899551
Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis o...

Sep 2017 28880184
Identifying sleep spindles with multichannel EEG and classification optimization.

Researchers classify critical neural events during sleep called spindles that are related to memory ...

Sep 2017 28886481
A New Method for Automatic Sleep Stage Classification.

Traditionally, automatic sleep stage classification is quite a challenging task because of the diffi...

Aug 2017 28809709
Deep learning with convolutional neural networks for EEG decoding and visualization.

Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision ...

Aug 2017 28782865
Mixed Neural Network Approach for Temporal Sleep Stage Classification.

This paper proposes a practical approach to addressing limitations posed by using of single-channel ...

Jul 2017 28767373
Phenomenological network models: Lessons for epilepsy surgery.

The current opinion in epilepsy surgery is that successful surgery is about removing pathological co...

Jul 2017 28744852
Human interaction with robotic systems: performance and workload evaluations.

We first tested the effect of differing tactile informational forms (i.e. directional cues vs. stati...

Jul 2017 28745552
Identifying seizure onset zone from electrocorticographic recordings: A machine learning approach based on phase locking value.

PURPOSE: Using a novel technique based on phase locking value (PLV), we investigated the potential f...

Jul 2017 28772200
EEG machine learning for accurate detection of cholinergic intervention and Alzheimer's disease.

Monitoring effects of disease or therapeutic intervention on brain function is increasingly importan...

Jul 2017 28720796
Feature selection before EEG classification supports the diagnosis of Alzheimer's disease.

OBJECTIVE: In many decision support systems, some input features can be marginal or irrelevant to th...

Jul 2017 28866471
A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD).

Major depressive disorder (MDD), a debilitating mental illness, could cause functional disabilities ...

Jul 2017 28702811
Synaptic damage underlies EEG abnormalities in postanoxic encephalopathy: A computational study.

OBJECTIVE: In postanoxic coma, EEG patterns indicate the severity of encephalopathy and typically ev...

Jul 2017 28753456
Automated Classification and Removal of EEG Artifacts With SVM and Wavelet-ICA.

Brain electrical activity recordings by electroencephalography (EEG) are often contaminated with sig...

Jul 2017 28692997
Time-Varying System Identification Using an Ultra-Orthogonal Forward Regression and Multiwavelet Basis Functions With Applications to EEG.

A new parametric approach is proposed for nonlinear and nonstationary system identification based on...

Jun 2017 28650829
A machine learning approach for automated wide-range frequency tagging analysis in embedded neuromonitoring systems.

EEG is a standard non-invasive technique used in neural disease diagnostics and neurosciences. Frequ...

Jun 2017 28647609
Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing.

Developing effective and affordable biomarkers for dementias is critical given the difficulty to ach...

Jun 2017 28630492
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