Neurology

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

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Decoding Parkinson's Diagnosis: An OCT-Based Explainable AI with SHAP/LIME Transparency from the Persian Cohort Study.

BACKGROUND: Parkinson's disease (PD) diagnosis remains challenging due to subjective clinical assess...

Optimizing stroke detection with genetic algorithm-based feature selection in deep learning models.

Brain stroke is a leading cause of disability and mortality worldwide, necessitating the development...

From neurotoxicity to neuroprotection: Rethinking GABAR-targeting anesthetics.

The brain growth spurt (BGS) represents a pivotal window in neurodevelopment, defined by rapid neuro...

Machine learning-based models for outcome prediction in skull base and spinal chordomas: a systematic review and meta-analysis.

BACKGROUND: Chordomas are primary bone lesions originating from embryonic notochord remnants, most c...

Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.

OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medici...

Prediction of NIHSS Scores and Acute Ischemic Stroke Severity Using a Cross-attention Vision Transformer Model with Multimodal MRI.

RATIONALE AND OBJECTIVES: This study aimed to develop and evaluate models for classifying the severi...

FedOcw: optimized federated learning for cross-lingual speech-based Parkinson's disease detection.

Accurate detection of Parkinson's disease (PD) through speech analysis holds great promise for early...

2D van der Waals heterostructure memristors: from band structure regulation to neuromorphic computing applications.

Two-dimensional (2D) materials and their van der Waals heterostructures (vdWHs) have shown tremendou...

Lumbar spinal stenosis: current concept of management.

Lumbar spinal stenosis (LSS) is a common degenerative spinal condition where spinal canal narrowing ...

Visualizing nuclear pore complex plasticity with pan-expansion microscopy.

The exploration of cell-type and environmentally responsive nuclear pore complex (NPC) plasticity re...

Precision-Optimised Post-Stroke Prognoses.

BACKGROUND: Current medicine cannot confidently predict who will recover from post-stroke impairment...

Optimizing Dementia Diagnosis Through Distance-Correlation Feature Space and Dimensionality Reduction.

The reduction of dimensionality in machine learning and artificial intelligence problems constitutes...

DBSCAN and DBCV application to open medical records heterogeneous data for identifying clinically significant clusters of patients with neuroblastoma.

Neuroblastoma is a common pediatric cancer that affects thousands of infants worldwide, especially c...

Regional and whole-brain neurofunctional alterations during pain empathic processing of physical but not affective pain in migraine patients.

BACKGROUND: Accumulating evidence suggests that migraine patients present abnormal brain responses t...

Clinical correlates of data-driven subtypes of deep gray matter atrophy and dopamine availability in early Parkinson's disease.

Recent machine-learning techniques may be useful to identify subtypes with distinct spatial patterns...

Machine Learning-Based Prediction of Delayed Neurological Sequelae in Carbon Monoxide Poisoning Using Automatically Extracted MR Imaging Features.

BACKGROUND AND PURPOSE: Delayed neurological sequelae are among the most serious complications of ca...

Emerging Trends in Artificial Intelligence in Neuro-Oncology.

PURPOSE OF REVIEW: This article explores the evolving role of artificial intelligence (AI) in neuro-...

Fusion of FDG and FMZ PET Reduces False-Positives in Predicting Epileptogenic Zone.

BACKGROUND AND PURPOSE: Epilepsy, a globally prevalent neurologic disorder, necessitates precise ide...

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