Neurology

Interpretable deep learning framework for understanding molecular changes in human brains with Alzheimer's disease: implications for microglia activation and sex differences.

The utilization of artificial intelligence in studying the dysregulation of gene expression in Alzhe...

Evaluating the Readability of Pediatric Neurocutaneous Syndromes-Related Patient Education Material Created by a Custom GPT With Retrieval Augmentation.

In our study, we developed a GPT assistant with a custom knowledge base for neurocutaneous diseases,...

VGRF Signal-Based Gait Analysis for Parkinson's Disease Detection: A Multi-Scale Directed Graph Neural Network Approach.

Parkinson's Disease (PD) is often characterized by abnormal gait patterns, which can be objectively ...

Integrated machine learning and deep learning-based virtual screening framework identifies novel natural GSK-3β inhibitors for Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder lacking effective therapies. Gl...

Distinguishing symptomatic and asymptomatic trigeminal nerves through radiomics and deep learning: A microstructural study in idiopathic TN patients and asymptomatic control group.

PURPOSE: The relationship between mild neurovascular conflict (NVC) and trigeminal neuralgia (TN) re...

Effects of volatile and intravenous anesthetics on postoperative cognitive dysfunction: a mechanistic review.

Postoperative cognitive dysfunction (POCD) is a common neurological complication after surgery, with...

Answer to the letter to the editor of T. Tu concerning "Machine learning-based models for outcome prediction in skull base and spinal chordomas: a systematic review and meta-analysis" by B. Hajikarimloo, et al. (Eur spine J [2025]: doi: 10.1007/s00586-025-09053-y).

EEG signal analysis for the classification of Alzheimer's and frontotemporal dementia: a novel approach using artificial neural networks and cross-entropy techniques.

Dementia, a neurological disorder, can cause cognitive decline due to damage to the brain. Our study...

Development of a risk prediction model for sepsis-related delirium based on multiple machine learning approaches and an online calculator.

BACKGROUND: Sepsis-associated delirium (SAD) occurs due to disruptions in neurotransmission linked t...

APOE ε4 carriers share immune-related proteomic changes across neurodegenerative diseases.

The APOE ε4 genetic variant is the strongest genetic risk factor for late-onset Alzheimer's disease ...

Objective monitoring of motor symptom severity and their progression in Parkinson's disease using a digital gait device.

Digital technologies for monitoring motor symptoms of Parkinson's Disease (PD) underwent a strong ev...

Motion artifacts and image quality in stroke MRI: associated factors and impact on AI and human diagnostic accuracy.

OBJECTIVES: To assess the prevalence of motion artifacts and the factors associated with them in a c...

Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.

Timely detection of cognitive decline is paramount for effective intervention, prompting researchers...

Exploring the mechanism of metabolic cell death-related genes AKR1C2 and MAP1LC3A as biomarkers in Parkinson's disease.

There is a strong relationship between metabolic cell death (MCD) and neurodegenerative diseases. Ho...

Deep adaptive learning predicts and diagnoses CSVD-related cognitive decline using radiomics from T-FLAIR: a multi-centre study.

Early identification of cerebral small vessel disease related cognitive impairment (CSVD-CI) is cruc...

Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models.

Positron Emission Tomography (PET) is a valuable imaging method for studying molecular-level process...

One Neuron Saved is One Neuron Earned: On Parametric Efficiency of Quadratic Networks.

Inspired by neuronal diversity in the biological neural system, a plethora of studies proposed to de...

DAFF-SNN: Dual Attention-driven and Feature Fusion-based Spiking Neural Network for Epilepsy Detection based on Electroencephalogram.

Electroencephalogram (EEG) signals provide rich spatiotemporal brain features crucial for epilepsy d...

Comparative effectiveness of anti-seizure medications in emulated trials using medical informatics.

Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar...

Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study.

BACKGROUND: Dementia is a progressive neurodegenerative condition that affects millions worldwide, o...

Development and Validation of a Large Language Model-Powered Chatbot for Neurosurgery: Mixed Methods Study on Enhancing Perioperative Patient Education.

BACKGROUND: Perioperative education is crucial for optimizing outcomes in neuroendovascular procedur...