Neurology

Explainable artificial intelligence-driven visual task-specific electroencephalogram analysis for attention deficit hyperactivity disorder detection using information-theoretic feature selection.

Attention deficit hyperactivity disorder (ADHD) is a neurological disorder that primarily develops i...

Can epilepsy be predicted after the first febrile seizure? Insights from machine learning of postictal EEG.

OBJECTIVE: Febrile seizures (FS) are the most common seizures in childhood, yet identifying children...

Advances in Cell Therapy for Neural Repair.

Neural repair remains one of the foremost challenges in modern neuroscience, as damage to the centra...

EEG-VLM: A Hierarchical Vision-Language Model With Multi-Level Feature Alignment and Visually Enhanced Language-Guided Reasoning for EEG Image-Based Sleep Stage Prediction.

Sleep stage classification based on electroencephalography (EEG) is fundamental for assessing sleep ...

Support vector machine-driven Parkinson's disease identification: a 7-Tesla multidimensional structural MRI approach.

Parkinson's disease (PD) is a progressive neurodegenerative disorder diagnosed clinically by cardina...

Modified graph neural network-oriented optimization model for the classification of PD.

Methods for categorizing Parkinson's Disease (PD) aim to automatically distinguish among healthy ind...

Unveiling an ALS Blood Transcriptomic Signature: A Machine Learning Classifier Distinct from Neurodegenerative Controls.

A cross-sectional protocol for experimental tongue high-density surface electromyography to detect and classify radiation-associated hypoglossal neuropathy.

BACKGROUND: Hypoglossal neuropathy is the most common lower cranial neuropathy detected as a delayed...

Functional evaluation in adult spinal deformity can be reduced to 3 key kinematic parameters that can sufficiently predict health-related quality of life outcomes: an observational prospective study.

BACKGROUND CONTEXT: Recently, functional evaluation using 3D gait analysis (3DGA) proved to predict ...

Neural estimates of language comprehension of sentences with selected action verbs in a non-literal context in the Polish language studied by permutation cluster-based analysis and decoding of the event-related potentials.

BACKGROUND: This work examines how the human brain processes mental metaphors in Polish verbal phras...

MotorQuant: A novel tool for motor function assessment in spinal cord injured mice.

The assessment of motor function recovery in spinal cord injury (SCI) mouse models traditionally rel...

Frequency Band Personalization for Seizure Network Analysis in Multifocal Patients.

Stereo-electroencephalography (SEEG) is commonly used for pre-surgical evaluation in patients with m...

Innovative therapies under clinical development for ALS treatment: Small molecules.

INTRODUCTION: The clinical trial landscape for Amyotrophic Lateral Sclerosis (ALS) is a rapidly evol...

Machine Learning-Based Risk Stratification for Symptomatic Intracranial Hemorrhage and 3-month Prognosis Following Intravenous Thrombolysis.

INTRODUCTION: Intravenous thrombolysis (IVT) with tissue-type plasminogen activator (tPA) is a corne...

Effects of a Soft Robotic Exoskeleton for Gait Training on Clinical Outcomes in Patients With Parkinson Disease: Randomized Controlled Pilot Study.

BACKGROUND: Balance and gait disorders in Parkinson disease (PD) impair motor function and quality o...

A Qualitative Exploration of Ethical Aspects of Using AI in Parkinson Disease: Patient Panel Study.

BACKGROUND: As Parkinson disease (PD) rates increase, so does interest in finding new technological ...

Cross-Subject Generalization for EEG Decoding: A Survey of Deep Learning Methods.

Deep learning for cross-subject EEG decoding is hindered by the high degree of inter-subject variabi...

Retraction Note: A novel approach integrating topological deep learning from EEG Data in Alzheimer's disease.

Coupled gradient-evolutionary learning in sparse memristive neuromorphic networks for robust edge intelligence.

To address fragmented multimodal perception, high energy consumption in hardware deployment, and del...

Unveiling the causal pathway of Parkinson's disease dysphonia: A voice causal generative model (VCGM) approach.

BACKGROUND: Although artificial intelligence (AI) models have demonstrated high accuracy in diagnosi...

Cognitive trajectories in early Parkinson's disease: A multimodal MRI study of brain structure and cognitive decline.

Cognitive trajectories in Parkinson's disease (PD) exhibit substantial heterogeneity, ranging from l...