Neurology

Progression and natural history of Atypical Parkinsonism (ATPARK): Protocol for a longitudinal follow-up study from an underrepresented population.

BACKGROUND: Atypical Parkinsonian Syndromes (APS) form the third largest group of neurodegenerative disorders including Progressive Supranuclear Palsy (PSP), Multiple System Atrophy (MSA), and Corticobasal Syndrome (CBS). These conditions are characterized by rapid progression, poor prognosis, low survival rates, and limited treatment options. Few studies have suggested that genetic, environmental...

A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection.

Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal brain activity, which can severely affects people's normal lives. To improve the lives of these patients, it is necessary to develop accurate methods to predict seizures. Electroencephalography (EEG), as a non-invasive and real-time technique, is crucial for the early diagnosis of epileptic seizures by monit...

Epilepsy Prediction via Time-Frequency Features and Multi-Scale Hybrid Neural Networks.

The prediction of epileptic seizures heavily depends on the precise embedding and classification of complex, multi-dimensional electroencephalogram (E...

Regional free-water diffusion is more strongly related to neuroinflammation than neurodegeneration.

INTRODUCTION: Recent research has suggested that neuroinflammation may be important in the pathogenesis of neurodegenerative diseases. Free-water diff...

CMOS LIF Neurons with Local Membrane Dynamic Biasing Based on Reciprocal Inhibition for Self-Oscillatory Neural Networks.

This paper presents a CMOS-based neuron network that can emulate self-oscillatory biasing behaviors found in biological neural oscillator models. Base...

Cerebral lateralization assessment: an explainable deep learning approach with channel attention mechanism.

In recent years, cross-frequency coupling (CFC) has emerged as a valuable tool in the study of a wide range of cognitive processes due to the strong e...

Association of peripheral immune markers with brain age and dementia risk estimated using deep learning methods.

BACKGROUND: The peripheral immune system is essential for maintaining central nervous system homeostasis. This study investigates the effects of perip...

Novel Application of Connectomics to the Surgical Management of Pediatric Arteriovenous Malformations.

Introduction The emergence of connectomics in neurosurgery has allowed for construction of detailed maps of white matter connections, incorporating bo...

ASO Author Reflections: Can Artificial Intelligence Improve Confidence and Timing in Recurrent Laryngeal Nerve Recognition?

Machine Learning-Based Risk Assessment of Myasthenia Gravis Onset in Thymoma Patients and Analysis of Their Correlations and Causal Relationships.

The study aims to utilize interpretable machine learning models to predict the risk of myasthenia gravis onset in thymoma patients and investigate the...

Development and Validation of Machine Learning Models for Predicting 7-Day Mortality in Critically Ill Patients with Traumatic Spinal Cord Injury: A Multicenter Retrospective Study.

BACKGROUND: Traumatic spinal cord injury (TSCI), a severe central nervous system injury, despite treatment advances, critically ill patients with TSCI...

Impact of proton versus photon radiotherapy on overall survival in the management of spinal chordoma and mortality risk prediction: a nationwide analysis.

PURPOSE: This study aims to provide a national-level insight into the optimal management of spinal chordoma, a type of rare and complicated malignancy...

Machine learning-driven national analysis for predicting adverse outcomes in intramedullary spinal cord tumor surgery.

UNLABELLED: Spinal tumors represent 15% of all central nervous system malignancies, with intramedullary spinal cord tumors (IMSCTs) being rare. Predom...

Novel insights from comprehensive analysis: The role of cuproptosis and peripheral immune infiltration in Alzheimer's disease.

BACKGROUND: Cuproptosis is increasingly recognized as an essential factor in the pathological process of Alzheimer's disease (AD). However, the specif...

Advances and Integrations of Computer-Assisted Planning, Artificial Intelligence, and Predictive Modeling Tools for Laser Interstitial Thermal Therapy in Neurosurgical Oncology.

Laser interstitial thermal therapy (LiTT) has emerged as a minimally invasive, MRI-guided treatment of brain tumors that are otherwise considered inop...

Neural network-based multi-task learning to assist planning of posterior spinal fusion surgery for adolescent idiopathic scoliosis.

PURPOSE: Posterior spinal instrumentation and fusion (PSF) is the gold standard for severe adolescent idiopathic scoliosis (AIS), yet instrumentation ...

Temporal Dynamics of APOE and TREM2 Expression in Microglial Activation of NMOSD Mouse Models.

Neuromyelitis optica spectrum disorder (NMOSD) is a severe autoimmune demyelinating disease characterized by recurrent neuroinflammation and disabilit...

Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach.

BACKGROUND: As the global population ages, the economic burden of dementia continues to rise. Social isolation-which includes limited social interacti...

Effectiveness and safety of AI-driven closed-loop systems in diabetes management: a systematic review and meta-analysis.

BACKGROUND: Diabetes is a metabolic disease that can lead to severe cardiovascular diseases and neuropathy. The associated medical costs and complicat...

Identification of Migraine Subtypes Using Functional Near-Infrared Spectroscopy Data: A Domain-Based Feature Extraction.

Migraine diagnosis relies on subjective patient reports and International Headache Society guidelines, leading to misdiagnoses. In clinical practice, ...