Neurology

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

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Inter-participant transfer learning with attention based domain adversarial training for P300 detection.

A Brain-computer interface (BCI) system establishes a novel communication channel between the human ...

Hybrid similarity based feature selection and cascade deep maxout fuzzy network for Autism Spectrum Disorder detection using EEG signal.

Autism Spectrum Disorder (ASD) is a neurological disorder that influences a person's comprehension a...

SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection.

Emotional recognition is highly important in the field of brain-computer interfaces (BCIs). However,...

A machine learning system for artificial ligaments with desired mechanical properties in ACL reconstruction applications.

The anterior cruciate ligament is one of the important tissues to maintain the stability of the huma...

XDL-ESI: Electrophysiological Sources Imaging via explainable deep learning framework with validation on simultaneous EEG and iEEG.

Electroencephalography (EEG) or Magnetoencephalography (MEG) source imaging aims to estimate the und...

Independent Vector Analysis for Feature Extraction in Motor Imagery Classification.

Independent vector analysis (IVA) can be viewed as an extension of independent component analysis (I...

Advanced Sensing System for Sleep Bruxism across Multiple Postures via EMG and Machine Learning.

Diagnosis of bruxism is challenging because not all contractions of the masticatory muscles can be c...

MLS-Net: An Automatic Sleep Stage Classifier Utilizing Multimodal Physiological Signals in Mice.

Over the past decades, feature-based statistical machine learning and deep neural networks have been...

Robotic assessment of bilateral and unilateral upper limb functions in adults with cerebral palsy.

BACKGROUND: Children with unilateral cerebral palsy (CP) exhibit motor impairments predominantly on ...

PVTAD: ALZHEIMER'S DISEASE DIAGNOSIS USING PYRAMID VISION TRANSFORMER APPLIED TO WHITE MATTER OF T1-WEIGHTED STRUCTURAL MRI DATA.

Alzheimer's disease (AD) is a neurodegenerative disorder, and timely diagnosis is crucial for early ...

Human hand gesture recognition using fast Fourier transform with coot optimization based on deep neural network.

Hand motion detection is particularly important for managing the movement of individuals who have li...

An efficient ANN SoC for detecting Alzheimer's disease based on recurrent computing.

Alzheimer's Disease (AD) is an irreversible, degenerative condition that, while incurable, can have ...

Continual learning for seizure prediction via memory projection strategy.

Despite extensive algorithms for epilepsy prediction via machine learning, most models are tailored ...

Benchmarking brain-computer interface algorithms: Riemannian approaches vs convolutional neural networks.

To date, a comprehensive comparison of Riemannian decoding methods with deep convolutional neural ne...

A minimalistic approach to classifying Alzheimer's disease using simple and extremely small convolutional neural networks.

BACKGROUND: There is a broad interest in deploying deep learning-based classification algorithms to ...

An Unsupervised Learning Tool for Plaque Tissue Characterization in Histopathological Images.

Stroke is the second leading cause of death and a major cause of disability around the world, and th...

Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning.

Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the und...

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