Results 91 to 100 of about 3,131,508 (227)
T1 Over Squared Proton Density Ratio to Characterize Multiple Sclerosis Lesions
ABSTRACT Objective Differentiating remyelinated from demyelinated lesions in MS remains challenging without histological confirmation. This study introduces the T1‐to‐PD2 ratio (TPR) imaging approach and evaluates its ability to characterize MS lesions alongside other quantitative MRI (qMRI) metrics. Methods Thirty individuals with MS (mean age: 47.5 ±
Sarah J. Wright +10 more
wiley +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Understanding How Image Quality Affects Transformer Neural Networks
Deep learning models, particularly transformer architectures, have revolutionized various computer vision tasks, including image classification. However, their performance under different types and levels of noise remains a crucial area of investigation.
Domonkos Varga
doaj +1 more source
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu +7 more
wiley +1 more source
White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy
ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram +3 more
wiley +1 more source
Introduction: Although noise characteristics such as intensity and frequency are the main cause of detrimental effects, it is important to pay attention to the personality traits of individuals as the host of adverse health effects. The aim of this study
Milad Abbasi +5 more
doaj
Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella +5 more
wiley +1 more source
Boundary‐Dependent Sleep–Wake Dysregulation in Idiopathic Hypersomnia
ABSTRACT Objective Idiopathic hypersomnia (IH) presents with excessive daytime sleepiness (EDS) despite apparently preserved nocturnal sleep, challenging traditional models of hypersomnolence based on sleep loss or fragmentation. We aimed to test the hypothesis that EDS in IH reflects excessive stabilization of the sleep state, consistent with ...
Samantha Mombelli +13 more
wiley +1 more source
In recent years, hybrid systems combining data-driven and physics-based approaches have gained increasing attention for solving complex real-world problems where deterministic modeling alone is insufficient. Within this framework, Physics-Informed Neural
Norbert Annuš, Tibor Kmeť
doaj +1 more source
Temporal Divergence of True and False Alarms in Pediatric Nocturnal Seizure Monitoring
The early‐morning surge in false seizure alarms supports exploring time‐ or state‐dependent detection thresholds to reduce false detections. ABSTRACT Seizure detection devices can improve the safety of children with epilepsy, yet high false alarms limit their clinical applicability.
Mohammad Shahbakhti +6 more
wiley +1 more source

