Neurology

Enriched resting-state EEG prediction of cognitive decline in prodromal Alzheimer's disease: a machine-learning approach.

OBJECTIVE: We evaluated the accuracy of standard machine learning (ML) algorithms in predicting 1-ye...

Perfusion-derived cerebral CT angiography with artificial intelligence iterative reconstruction as a replacement for routine cerebral CT angiography in acute ischemic stroke.

OBJECTIVES: To investigate the feasibility of replacing routine cerebral CT angiography (CTA) with C...

Hippocampal-parietal directed connectivity mediates brain network reconfiguration between internal and external attention: An intracranial EEG study.

Attention is a cornerstone of cognitive function, and understanding its neural mechanisms is of grea...

Ultrastructural Evidence of Altered Dendritic Morphology in the Prefrontal Cortex of Alzheimer's Model Rats.

Alzheimer's disease (AD) is a neurodegenerative disorder with synaptic pathology as a core theme in ...

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.

BACKGROUND: Early detection of Alzheimer disease (AD) is essential for timely intervention; yet, dia...

Effectiveness of Thoracic Paravertebral Block in Minimally Invasive Vertebroplasty: A Retrospective Cohort Study Focusing on Pain Trajectories and Sagittal Spinal Alignment.

PURPOSE: To evaluate the effectiveness of ultrasound-guided thoracic paravertebral block (TPVB) comb...

Nonlinear dynamical analysis of chaos, fractal complexity, and entropy in EEG signals during music therapy in ICU burn patients.

Music therapy (MT) is known to influence brain dynamics; however, its effects on nonlinear electroen...

Robot-Assisted Therapy for Upper Limb Rehabilitation After Stroke: Umbrella Review.

BACKGROUND: Stroke is a leading cause of long-term upper limb disability, severely impacting patient...

Personalized prediction of initial valproic acid dose in children with epilepsy using machine learning techniques.

INTRODUCTION: Valproic acid (VPA) is widely prescribed antiepileptic drug in children because of its...

EEG-RCPNet: a cross-subject cognitive impairment detection model based on limited-channel eeg signals.

Development and validation of a prediction model for long-term cognitive frailty risk in stroke patients based on CHARLS data.

BACKGROUND: This study aimed to develop and validate machine learning (ML) models for predicting the...

Establishment of a novel deep learning-based method for gait analysis after peripheral nerve injury in pigs.

BACKGROUND: Peripheral nerve injury with deficits has poor functional prognosis, making motor functi...

Automated estimation of perivascular space and brain morphometry from deep learning-reconstructed three-dimensional T1-weighted MRI: comparison with the conventional technique.

PURPOSE: To evaluate the utility of deep learning-based reconstruction (DLR) three-dimensional T1-we...

Optimized Complex-Valued Spatio-Temporal Graph Convolutional Networks for attention deficit hyperactivity disorder detection in pediatric EEG signals.

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental condition affecting mood, an...

Prediction of depressive episodes based on clinical features, cognitive characteristics, inflammation-related proteins, and EEG data.

The absence of clinically validated biomarkers and objective diagnostic protocols hinders the accura...

A vision transformer model for the detection of glaucoma from optic disc photographs.

This study uses a deep learning algorithm to analyze optic disc photographs (ODPs) and classify eyes...

Multi-output LSTM-based prediction of postoperative delirium: integrating baseline and perioperative data for enhanced risk stratification in older spine surgery patients.

INTRODUCTION: Postoperative delirium (POD) adversely affects clinical outcomes among older adults un...

Ti3C2/CuCoSe2 p-n Heterojunction: Preparation and Mechanism for Machine Learning-enhanced Electrochemical Sensing of Rutin.

Rutin is widely employed as a therapeutic agent, but excessive intake may induce adverse reactions s...

Research on Alzheimer's Disease Risk Assessment Models and Biomarker Screening Based on Bioinformatics Analysis and Machine Learning Algorithms.

INTRODUCTION: Alzheimer's Disease (AD) is among the most prevalent neurodegenerative disorders globa...

Emerging Roles of Small-molecule Derivatives in Modulating Neurodegenerative Pathways: From Molecular Targets to Therapeutic Applications.

Neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sc...

Reimagining Brain Drug Delivery: Mechanistic and Translational Advances in Carbon Nanotube Nanomedicine.

Neurological and neurodegenerative disorders (NDDs) present ongoing therapeutic challenges attribute...