Neurology

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

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Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network.

Previous deep learning-based brain network research has made significant progress in understanding t...

Specific endophenotypes in EEG microstates for methamphetamine use disorder.

BACKGROUND: Electroencephalogram (EEG) microstates, which reflect large-scale resting-state networks...

Enhanced electroencephalogram signal classification: A hybrid convolutional neural network with attention-based feature selection.

Accurate recognition and classification of motor imagery electroencephalogram (MI-EEG) signals are c...

Multi-knowledge informed deep learning model for multi-point prediction of Alzheimer's disease progression.

The diagnosis of Alzheimer's disease (AD) based on visual features-informed by clinical knowledge ha...

Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging.

INTRODUCTION: Altered neurometabolism is an important pathological mechanism in many neurological di...

Multi-branch convolutional neural network with cross-attention mechanism for emotion recognition.

Research on emotion recognition is an interesting area because of its wide-ranging applications in e...

Machine learning techniques for independent gait recovery prediction in acute anterior circulation ischemic stroke.

OBJECTIVE: This study aimed to develop and validate a machine learning-based predictive model for ga...

HEDDI-Net: heterogeneous network embedding for drug-disease association prediction and drug repurposing, with application to Alzheimer's disease.

BACKGROUND: The traditional process of developing new drugs is time-consuming and often unsuccessful...

External validation of 12 existing survival prediction models for patients with spinal metastases.

BACKGROUND CONTEXT: Survival prediction models for patients with spinal metastases may inform patien...

Machine Learning and Experiments Revealed Key Genes Related to PANoptosis Linked to Drug Prediction and Immune Landscape in Spinal Cord Injury.

Spinal cord injury (SCI) is a severe central nervous system injury without effective therapies. PANo...

Differential diagnosis of multiple system atrophy with predominant parkinsonism and Parkinson's disease using neural networks (part II).

Neural networks (NNs) possess the capability to learn complex data relationships, recognize inherent...

Unveiling encephalopathy signatures: A deep learning approach with locality-preserving features and hybrid neural network for EEG analysis.

EEG signals exhibit spatio-temporal characteristics due to the neural activity dispersion in space o...

Identification of therapeutic targets for Alzheimer's Disease Treatment using bioinformatics and machine learning.

Alzheimer's disease (AD) is a complex neurodegenerative disorder that currently lacks effective trea...

Preoperative anemia is an unsuspecting driver of machine learning prediction of adverse outcomes after lumbar spinal fusion.

BACKGROUND CONTEXT: Preoperative risk assessment remains a challenge in spinal fusion operations. Pr...

Artificial intelligent based control strategy for reach and grasp of multi-objects using brain-controlled robotic arm system.

Brain-controlled robotic arm systems are designed to provide a method of communication and control f...

Graph convolution network-based eeg signal analysis: a review.

With the advancement of artificial intelligence technology, more and more effective methods are bein...

Adjacent point aided vertebral landmark detection and Cobb angle measurement for automated AIS diagnosis.

Adolescent Idiopathic Scoliosis (AIS) is a prevalent structural deformity disease of human spine, an...

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