Neurology

Comparative study of radiomics features between ASL and DSC perfusion-weighted imaging in distinguishing radiation-induced brain injury from glioma recurrence.

OBJECTIVE: To compare the radiomics features of pseudocontinuous arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) perfusion-weighted imaging in distinguishing radiation-induced brain injury (RIBI) from tumor recurrence (TR) in patients with diffuse gliomas. MATERIALS AND METHODS: A total of 131 patients with pathologically confirmed adult-type diffuse gliomas, presenting with...

Reference Standards, Numerical Consistency, and Scoring Logic: Pre-deployment Assurance Considerations for AI-Assisted Third Molar Extraction Planning : Regarding: Ko J, Sooksatra S, Kim S, Tang S, Ha JE, Han DH, Lee KH, Jung YJ, Kim MJ. Quantitative assessment of third molar extraction difficulty and nerve injury risk using artificial intelligence and image processing. Ann Biomed Eng. 2026. https://doi.org/10.1007/s10439-026-04114-9.

Graph Convolutional Neural Network based Depression Detection using Brain Functional Connectivity Measures.

The structural and functional connectivity of the brain network is a combination of complex connections and interconnections among neurons of differen...

Comparative Outcomes of a Pediatric Walking Rehabilitation Robot Combined With Repetitive Transcranial Magnetic Stimulation in Children With Spastic Cerebral Palsy: Protocol for a Prospective Observational Study.

BACKGROUND: Cerebral palsy (CP) is a prevalent neurodevelopmental disorder in children, often leading to long-term motor impairments. Rehabilitation r...

An improved catch fish optimization based deep learning model for Parkinson disease classification using EEG signal.

Accurate and objective identification of Parkinson's Disease (PD) from Electroencephalogram (EEG) signals is important because EEG responses are compl...

Moving artificial intelligence from research to real-world clinical use in neurology.

Artificial intelligence (AI) applications in neurology have reached an inflection point. Despite US Food and Drug Administration approval of numerous ...

Metaheuristic hyperparameter optimization of deep neural networks for demographic-aware autism spectrum disorder classification.

Autism Spectrum Disorder (ASD) classification from neuroimaging data poses significant challenges due to high data heterogeneity and the complexity of...

Identification of biomarkers of cerebral infarction related to ferroptosis and ubiquitin-proteasome system based on transcriptomics and the experimental validation.

Cerebral infarction is a neurological disease with complex pathological mechanisms. This study aimed to explore the association between ferroptosis-re...

Facial phenotypes in Alzheimer's disease: from neurobiology to artificial intelligence.

Facial analysis is increasingly being explored as a source of scalable behavioral signals relevant to Alzheimer's disease (AD) and AD-related cognitiv...

Deep contrastive learning framework identifies cell-type-specific drug targets in Alzheimer's disease.

INTRODUCTION: Identifying disease-modifying drug targets is crucial for developing effective Alzheimer's disease (AD) treatments. METHODS: We present ...

Artificial intelligence in headache care.

Cochlear aging after synaptopathic noise: age-noise interactions in hair cell loss and axonal degeneration.

Despite many studies of cochlear synaptic loss and/or recovery after acoustic injury, none has followed degeneration of auditory-nerve fiber (ANF) per...

Abrupt Scene Onsets and Gradually Emerging Scene Information Produce Distinct EEG Decoding Dynamics.

Multivariate analyses of M/EEG data are typically performed on neural responses time-locked to discrete stimulus onsets. Such designs usually reveal h...

Advances in 3D cell culture models for alzheimer's disease drug discovery.

INTRODUCTION: Alzheimer's Disease (AD) affects more than 57 million people, yet drug development faces high failure rates due to the limited translati...

Orchestrator multi-agent clinical decision support system for secondary headache diagnosis in primary care.

OBJECTIVE: Secondary headaches require urgent recognition due to potentially devastating consequences if untreated. Despite established clinical "red ...

Integrated machine learning, molecular docking, and molecular dynamics simulations for in silico identification of GSK3β inhibitors for Alzheimer's disease.

Glycogen Synthase Kinase-3 Beta is a multifunctional serine/threonine kinase, involved in regulating multiple cellular processes. Its dysregulation pl...

Machine learning classification and regional differentiation of neuropathologically-confirmed Alzheimer's disease and comorbid Lewy body disease.

BACKGROUND: Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) co-occur frequently, and growing evidence, including neuropathology, supports...

A Robust Voice-Based Parkinson's Disease Diagnosis Model via Semantic RGB Feature Transformation and Hybrid Deep Learning.

Reliable diagnosis of Parkinson's disease (PD) in its early stages is of vital importance for supporting timely clinical decision-making and improving...

The natural isoflavone puerarin mitigates cerebral ischemia-reperfusion injury by directly targeting CaMKⅡδ to block DLG4-Ser654 phosphorylation.

BACKGROUND: Synaptic collapse drives severe neurological deficits following cerebral ischemia-reperfusion (I/R) injury. Puerarin, a bioactive isoflavo...

An EMI-suppressed, high-fidelity Janus bioelectrode with gradient impedance for accurate dual-biosignal-based motion recognition.

Accurate acquisition of bioelectrical signals like electromyography (EMG) and electrocardiography (ECG) is essential for wearable health monitoring an...