Results 151 to 160 of about 8,336,119 (285)

Stage‐Specific Patterns of Imaging and Non‐Motor Biomarkers in Spinocerebellar Ataxia Type 3

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Advancements in disease‐modifying therapies for spinocerebellar ataxia Type 3 (SCA3) underscore the need for robust biomarkers to monitor disease progression and evaluate treatment efficacy. Although motor phenotypes have been well characterized, less is known about non‐motor and imaging‐based features across different disease stages.
Chun Li   +17 more
wiley   +1 more source

Automatic Lesion Morphometrics Reliably Predict Sensorimotor Recovery After Spinal Cord Injury: A Longitudinal, Multicenter Neuroimaging Study

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate automatic magnetic resonance imaging (MRI)‐derived lesion morphometrics against manual measurements and their prognostic value for characterizing distinct acute to chronic neurological recovery trajectories after spinal cord injury (SCI). Methods We studied a retrospective, multicenter cohort of cervical and thoracolumbar
Dario Pfyffer   +28 more
wiley   +1 more source

Molecular Diagnosis in Children With Febrile Seizures: Beyond the Conventional Clinical Classification

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Febrile seizures (FS) are currently classified as simple or complex primarily to describe seizure characteristics, with limited ability to identify the underlying etiology. We evaluated whether molecular diagnosis could complement conventional classification and improve the diagnosis and management of FS.
Jia Wang   +22 more
wiley   +1 more source

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

open access: yesArthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos   +2 more
wiley   +1 more source

Study of organic light-emitting diodes with internal light extraction structure

open access: yes, 2016
In this study, we fabricated organic light-emitting diodes (OLEDs) with internal light extraction structure to reduce the Waveguide mode loss and increase the EQE by using the Anti-Reflection (AR) and Photonic Quasi Crystals (PQC) micro-structure ...
Hong, Pei-Yuan
core  

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

open access: yesArthritis Care &Research, EarlyView.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil   +7 more
wiley   +1 more source

The Association of Gout Flare Resolution With Physical Activity and Sleep: A Prospective Remote‐Monitoring Study

open access: yesArthritis Care &Research, EarlyView.
Objective This study aimed to determine whether gout flare resolution is associated with physical activity and sleep. These findings were intended to inform the future development of a definition for flare resolution. Methods Data from 81 participants with gout who experienced at least one flare during a six‐month prospective observational study were ...
Sarah Stewart   +12 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli   +3 more
wiley   +1 more source

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