Neurology

Editorial: Application of machine learning in the diagnosis of dementia, volume II.

Use of artificial intelligence in the management of stroke: scoping review.

INTRODUCTION: Stroke is a condition that is more predominant in developed countries. However, it con...

Development and validation of a machine-learning model for the risk of potentially inappropriate medications in elderly stroke patients.

OBJECTIVE: To construct a risk prediction model for potentially inappropriate medications (PIM) in e...

Potential Function-Based Molecular Dynamics Simulation of Al-Cu-Li Alloys and Comparison with Experiments.

Due to their excellent specific strength and lightweight characteristics, Al-Cu-Li alloys are widely...

Random field image representations speed up binary discrimination of brain scans and estimate a phenotype glioblastoma cancer cell model.

MRI brain scans alone are not a definitive measure of dementia. Deep-learning algorithms (DLA) and p...

Assessment of contour accuracy in head and neck replanning: Deep learning trained model compared with deformable image registration propagation technique.

Accurate contouring is crucial for optimal treatment outcomes, whether for nonadaptive radiotherapy ...

Novel Voice Signal Segmentation Based on Clark Distance to Improve Intelligent Parkinson Disease Detection.

This paper presents a novel classifier based on the Clark distance for early detection of Parkinson'...

Identification of shared mechanisms between Alzheimer's disease and atherosclerosis by integrated bioinformatics analysis.

Alzheimer's disease (AD) and atherosclerosis (AS) are two interacting diseases mostly affecting aged...

A Novel Dynamic Neural Network for Heterogeneity-Aware Structural Brain Network Exploration and Alzheimer's Disease Diagnosis.

Heterogeneity is a fundamental characteristic of brain diseases, distinguished by variability not on...

NSSI-Net: A Multi-Concept GAN for Non-Suicidal Self-Injury Detection Using High-Dimensional EEG in a Semi-Supervised Framework.

Non-suicidal self-injury (NSSI) is a serious threat to the physical and mental health of adolescents...

AlphaGrad: Normalized Gradient Descent for Adaptive Multi-loss Functions in EEG-based Motor Imagery Classification.

In this study, we propose AlphaGrad, a novel adaptive loss blending strategy for optimizing multi-ta...

Ambient technology in epilepsy clinical practice.

The utilization of large language model-based artificial intelligence (AI) in the field of neurology...

Artificial intelligence in neuro-oncology: methodological bases, practical applications and ethical and regulatory issues.

Artificial Intelligence (AI) is transforming neuro-oncology by enhancing diagnosis, treatment planni...

Multimodal MRI radiomics enhances epilepsy prediction in pediatric low-grade glioma patients.

BACKGROUND: Determining whether pediatric patients with low-grade gliomas (pLGGs) have tumor-related...

Older people and stroke: a machine learning approach to personalize the rehabilitation of gait.

INTRODUCTION: Stroke is a significant global public health challenge, ranking as the second leading ...

Classification of neurodegenerative diseases using brain effective connectivity and machine learning techniques: a systematic review.

BACKGROUND: Effective connectivity (EC) refers to the directional influences or causal relationships...

Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson's Disease: A Systematic Review and Meta-Analysis.

To evaluate the diagnostic accuracy of machine learning-assisted magnetic resonance imaging (MRI) in...

Bidirectional Phosphorescent Neuroplasticity for All-Optical Neurovision.

All-optical neuromorphics that can capture, process, and output photonic signals are in prospect to ...

High-Performance Ferroelectric Field-Effect Transistors Based on Ultrathin Indium Oxide for Neuromorphic Computing.

The emergence of artificial intelligence has revealed the limitations of traditional von Neumann com...

Surface Electromyography Combined with Artificial Intelligence in Predicting Neuromuscular Falls in the Elderly: A Narrative Review of Present Applications and Future Perspectives.

: Falls among the elderly are a major public health concern, leading to increased disability and mor...

Digital Biomarkers and AI for Remote Monitoring of Fatigue Progression in Neurological Disorders: Bridging Mechanisms to Clinical Applications.

Digital biomarkers for fatigue monitoring in neurological disorders represent an innovative approach...