Neurology

Seizures

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

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Showing 2605-2625 of 4,550 articles
A Semi-Supervised Few-Shot Learning Model for Epileptic Seizure Detection.

In the past decade, the rapid development of machine learning has dramatically improved the performa...

Nov 2021 34891365
Deep Learning End-to-End Approach for the Prediction of Tinnitus based on EEG Data.

Tinnitus is attributed by the perception of a sound without any physical source causing the symptom....

Nov 2021 34891415
Towards Deeper Neural Networks for Neonatal Seizure Detection.

Machine learning and more recently deep learning have become valuable tools in clinical decision mak...

Nov 2021 34891440
Schizophrenia Detection in Adolescents from EEG Signals using Symmetrically weighted Local Binary Patterns.

Schizophrenia is one of the most complex of all mental diseases. In this paper, we propose a symmetr...

Nov 2021 34891449
Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral Features.

The success of deep learning in computer vision has inspired the scientific community to explore new...

Nov 2021 34891466
EEG-GNN: Graph Neural Networks for Classification of Electroencephalogram (EEG) Signals.

Convolutional neural networks (CNN) have been frequently used to extract subject-invariant features ...

Nov 2021 34891471
A comparative study of AI systems for epileptic seizure recognition based on EEG or ECG.

The majority of studies for automatic epileptic seizure (ictal) detection are based on electroenceph...

Nov 2021 34891722
Classification of Epileptic Seizure From EEG Signal Based on Hilbert Vibration Decomposition and Deep Learning.

A convolution neural network (CNN) architecture has been designed to classify epileptic seizures bas...

Nov 2021 34891831
Seizure Type Classification Using EEG Based on Gramian Angular Field Transformation and Deep Learning.

classification of seizure types plays a crucial role in diagnosis and prognosis of epileptic patient...

Nov 2021 34891955
Single feature spatio-temporal architecture for EEG Based cognitive load assessment.

The study of electroencephalography (EEG) data for cognitive load analysis plays an important role i...

Nov 2021 34892044
Acoustic Based Footstep Detection in Pervasive Healthcare.

Passive detection of footsteps in domestic settings can allow the development of assistive technolog...

Nov 2021 34892324
EEG-Based Emotion Recognition for Modulating Social-Aware Robot Navigation.

Companion robots play an important role to accompany humans and provide emotional support, such as r...

Nov 2021 34892417
EEG-based Emotion Recognition Using Graph Convolutional Network with Learnable Electrode Relations.

Emotion recognition based on electroencephalography (EEG) plays a pivotal role in the field of affec...

Nov 2021 34892474
Reduction of the ERP Measurement Time by a Weighted Averaging Using Deep Learning.

In clinical examination, event-related potentials (ERPs) are estimated by averaging across multiple ...

Nov 2021 34892506
Demonstrating the Viability of Mapping Deep Learning Based EEG Decoders to Spiking Networks on Low-powered Neuromorphic Chips.

Accurate and low-power decoding of brain signals such as electroencephalography (EEG) is key to cons...

Nov 2021 34892509
Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram.

Traumatic Brain Injury (TBI) is a highly prevalent and serious public health concern. Most cases of ...

Nov 2021 34892516
[An anesthesia depth computing method study based on wavelet transform and artificial neural network].

General anesthesia is an essential part of surgery to ensure the safety of patients. Electroencephal...

Oct 2021 34713651
Assessment of obstructive sleep apnea-related sleep fragmentation utilizing deep learning-based sleep staging from photoplethysmography.

STUDY OBJECTIVES: To assess the relationship between obstructive sleep apnea (OSA) severity and slee...

Oct 2021 34089616
Towards Interpretable Machine Learning in EEG Analysis.

In this paper a machine learning model for automatic detection of abnormalities in electroencephalog...

Sep 2021 34545817
An end-to-end heterogeneous graph representation learning-based framework for drug-target interaction prediction.

Accurately identifying potential drug-target interactions (DTIs) is a key step in drug discovery. Al...

Sep 2021 33517357
Application of bi-modal signal in the classification and recognition of drug addiction degree based on machine learning.

Most studies on drug addiction degree are made based on statistical scales, addicts' account, and su...

Aug 2021 34517564
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