Neurology

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

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G-Protein Signaling in Alzheimer's Disease: Spatial Expression Validation of Semi-supervised Deep Learning-Based Computational Framework.

Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzhei...

Multimodal Machine Learning for Stroke Prognosis and Diagnosis: A Systematic Review.

Stroke is a life-threatening medical condition that could lead to mortality or significant sensorimo...

A General DNA-Like Hybrid Symbiosis Framework: An EEG Cognitive Recognition Method.

In electroencephalogram (EEG) cognitive recognition research, the combined use of artificial neural ...

Anatomic Interpretability in Neuroimage Deep Learning: Saliency Approaches for Typical Aging and Traumatic Brain Injury.

The black box nature of deep neural networks (DNNs) makes researchers and clinicians hesitant to rel...

Revolutionizing spinal interventions: a systematic review of artificial intelligence technology applications in contemporary surgery.

Leveraging its ability to handle large and complex datasets, artificial intelligence can uncover sub...

Classification of EEG evoked in 2D and 3D virtual reality: traditional machine learning versus deep learning.

. Virtual reality (VR) simulates real-life events and scenarios and is widely utilized in education,...

Task-oriented EEG denoising generative adversarial network for enhancing SSVEP-BCI performance.

The quality of electroencephalogram (EEG) signals directly impacts the performance of brain-computer...

Machine learning for forecasting initial seizure onset in neonatal hypoxic-ischemic encephalopathy.

OBJECTIVE: This study was undertaken to develop a machine learning (ML) model to forecast initial se...

Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap.

BACKGROUND AND OBJECTIVES: Disentangling brain aging from disease-related neurodegeneration in patie...

Prediction and clustering of Alzheimer's disease by race and sex: a multi-head deep-learning approach to analyze irregular and heterogeneous data.

Early detection of Alzheimer's disease (AD) is crucial to maximize clinical outcomes. Most disease p...

Design of EEG based thought identification system using EMD & deep neural network.

Biological communication system for neurological disorder patients is similar to the Brain Computer ...

Identification of novel markers for neuroblastoma immunoclustering using machine learning.

BACKGROUND: Due to the unique heterogeneity of neuroblastoma, its treatment and prognosis are closel...

A protocol for trustworthy EEG decoding with neural networks.

Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performanc...

Enhancing Efficiency with an AI-Augmented Clinician in Neurology.

Integrating artificial intelligence (AI) technologies into neurology promises increased patient acce...

NSSC: a neuro-symbolic AI system for enhancing accuracy of named entity recognition and linking from oncologic clinical notes.

Accurate recognition and linking of oncologic entities in clinical notes is essential for extracting...

Use of Artificial Intelligence in Cobb Angle Measurement for Scoliosis: Retrospective Reliability and Accuracy Study of a Mobile App.

BACKGROUND: Scoliosis is a spinal deformity in which one or more spinal segments bend to the side or...

Review of deep representation learning techniques for brain-computer interfaces.

In the field of brain-computer interfaces (BCIs), the potential for leveraging deep learning techniq...

Unsupervised learning for real-time and continuous gait phase detection.

Individuals with lower limb impairment after a stroke or spinal cord injury require rehabilitation, ...

AlzyFinder: A Machine-Learning-Driven Platform for Ligand-Based Virtual Screening and Network Pharmacology.

Alzheimer's disease (AD), a prevalent neurodegenerative disorder, presents significant challenges in...

A modified deep learning method for Alzheimer's disease detection based on the facial submicroscopic features in mice.

Alzheimer's disease (AD) is a chronic disease among people aged 65 and older. As the aging populatio...

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