Neurology

Cellular Senescence of Patient-derived Fibroblasts Reveals the Mid-old Stage as a Critical Window for Transcriptomic Signatures Linked to Alzheimer's Disease Biomarkers and Classification.

OBJECTIVE: Alzheimer's disease (AD) is strongly associated with aging, yet the interactions remain unclear. This study modeled replicative senescence in patient-derived fibroblasts to compare gene expression between AD dementia and controls across senescence stages and to evaluate whether stage-specific alterations reflect disease characteristics with diagnostic implications. METHODS: Dermal fibro...

Development and validation of a deep learning-based automatic segmentation and classification of cerebral white matter hyperintensities.

OBJECTIVES: White matter hyperintensities (WMH) represent neuroimaging markers of cerebral small vessel disease. We aimed to develop and validate a deep learning-based simultaneous, automatic WMH segmentation and classification model in patients with cognitive impairment. MATERIALS AND METHODS: This retrospective study included images from consecutive patients with cognitive impairment from a tert...

Machine learning-guided repurposing of FDA-approved quinolones as dual cholinesterase inhibitors: A multi-level docking, molecular dynamics, DFT, and SHAP-based analysis.

Alzheimer's disease (AD) involves progressive cholinergic degeneration, with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) playing key ...

Efficacy and comparative performance of machine learning models for stroke risk prediction in hypertensive patients: A systematic review and meta-analysis.

BACKGROUND: Stroke poses a significant health burden among hypertensive patients, where traditional risk models often lack precision. Machine learning...

A subject-based association network defines new pediatric sleep apnea phenotypes with different odds of recovery after treatment.

BACKGROUND AND OBJECTIVES: Timely treatment of pediatric obstructive sleep apnea (OSA) can prevent or reverse neurocognitive and cardiovascular morbid...

Optimising Sleep Stage Detection Using a Minimal Non-EEG Physiological Signal Set and Deep Learning.

Automatic sleep stage classification is essential for enabling non-invasive, at-home monitoring. However, current methods often rely on electroencepha...

Neuroanatomical-based machine learning prediction of Alzheimer's Disease across sex and age.

Alzheimer's Disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline and memory loss. In 2024 it affected approxima...

A review of deep learning techniques in Alzheimer's disease with emphasis on data tools and transfer learning.

Alzheimer's disease (AD) is a significant neurological condition that is marked by the gradual decline of memory and cognitive function, with a higher...

Artificial intelligence in lower limb joint moment prediction during typically developed gait: A systematic review and multilevel random-effects meta-analysis.

OBJECTIVE: Artificial intelligence (AI) methods have been widely applied in gait analysis, yet quantitative comparisons across models and their input-...

Brain connectivity predict surgical outcomes of low-grade epilepsy-associated neuroepithelial tumors.

OBJECTIVE: Low-grade epilepsy-associated neuroepithelial tumors (LEATs) often cause drug-resistant epilepsy. Despite complete resection of these lesio...

Mind the Gap! What do people with epilepsy want to know?

BACKGROUND: There is little research about the questions asked by people with epilepsy, and how these are answered. Information sources include standa...

Performance of deep-learning reconstruction combined with metal artifact reduction algorithm for dual-energy computed tomography angiography in intracranial aneurysm coil embolization.

PURPOSES: To evaluate the diagnostic confidence in cerebral aneurysm embolization coil follow-up using the deep learning image reconstruction (DLIR) b...

DLS-SUC: A precision prediction framework for lysine succinylation sites integrating the protein language model (ESM-2) and dual imbalance strategies.

Lysine succinylation (Ksucc), a negatively charged post-translational modification, plays a crucial role in regulating protein function, cellular sign...

The Influence of Sport Representation and Attitudes Toward Strength Training on Neuromuscular Performance Profiles in University Athletes: Part II Male Athletes.

McClean, ZJ, da Silva Torres, R, Herzog, W, Pasanen, K, Lun, V, and Jordan, MJ. The influence of sport representation and attitudes toward strength tr...

Effect of a Robot Pet Companion on the Mood of Older Adults Receiving Family Caregiver Support: Pilot RCT.

BACKGROUND AND OBJECTIVES: Use of companion robot pets to reduce social isolation and loneliness in older people is well-established. Outcomes associa...

mModPoEs: Multimodal posture estimation and feedback-driven correction of load-bearing human movements using wearable sensors and computer vision.

OBJECTIVE: Improper spinal posture during activities of daily living such as seated posture, upright stance, and ambulation, particularly under load-b...

Toward AI-Powered Neurovascular Intervention: From Imaging to XR-Robotic Convergence.

Stroke remains a leading cause of mortality and long-term disability worldwide, where rapid diagnosis and timely intervention are critical for improvi...

Development and Validation of an Interpretable Machine Learning Model for Predicting Early Fusion After Anterior Cervical Discectomy and Fusion.

STUDY DESIGN: Retrospective case-control study. OBJECTIVES: This study aimed to develop and preliminarily validate a machine learning (ML) model for p...

Enzyme-based biosensors: emerging tools for advanced biomedical applications.

Proteins and enzymes are fundamental elements for the correct regulation of cell metabolism and their dysregulation or malfunction can lead to the ons...

Factors associated with rapid spinal radiographic progression in patients with axial spondyloarthritis: A hospital-based retrospective cohort study with mSASSS scoring using deep learning model.

OBJECTIVE: To identify associated and protective factors of rapid spinal radiographic progression in axial spondyloarthritis (axSpA) using artificial ...