Results 141 to 150 of about 3,531,799 (287)

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
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

State of Oregon, ITSM Academy, CMDB session report

open access: yes, 2007
This archived document is maintained by the Oregon State Library as part of the Oregon Documents Depository Program. It is for informational purposes and may not be suitable for legal purposes.Title from PDF title page (viewed on Mar.

core  

Column research council: proceedings 1970 [PDF]

open access: yes, 1970
The purposes of Column Research Council are to study and discuss problems related to the stability and strength of metal compression members; to organize research in this field; to disseminate information; and to formulate design rules for consideration ...
Column Research Council
core  

Systemic Extracerebral Atherosclerotic Burden and Dementia Risk After Incident Stroke

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Stroke survivors are at increased risk of dementia, but clinically accessible markers of risk heterogeneity remain limited. Previous studies have largely examined atherosclerotic disease in individual vascular beds rather than the overall burden of systemic extracerebral atherosclerosis.
Zhexuan Yu   +4 more
wiley   +1 more source

Cracking the Code: Which Ocular Symptoms Predict Dry Eye Signs? Insights From a Large International Sicca Registry

open access: yesArthritis Care &Research, EarlyView.
Objective The study aimed to identify symptom‐based predictors of dry eye disease (DED) signs in the Sjögren's International Collaborative Clinical Alliance (SICCA) cohort. Methods We performed a retrospective analysis examining 16 ocular symptoms (most graded 0–4) and artificial tear (AT) use (graded 0–3) as predictors of DED signs (abnormal ocular ...
Pragnya R. Donthineni   +7 more
wiley   +1 more source

A Scoping Review and Meta‐Analysis of Proportions of Central Nervous System Manifestations Reported in Patients with Sjögren's Disease

open access: yesArthritis Care &Research, Accepted Article.
Objective The objective of this scoping review was to synthesize evidence on the proportion of individuals living with Sjögren's disease who experience central nervous system (CNS) manifestations. Methods We searched MEDLINE (via PubMed) and Embase from 1980 through January 29, 2026, and the ECRI Guidelines Trust from 2020 through January 29, 2026 ...
Arun Varadhachary   +21 more
wiley   +1 more source

Real‐World Effectiveness and Safety of Secukinumab in Giant Cell Arteritis: An Italian Multicenter Cohort Study

open access: yesArthritis Care &Research, EarlyView.
Objective The objective of this study was to evaluate the real‐world effectiveness and safety of secukinumab in patients with giant cell arteritis (GCA). Methods This multicenter retrospective study included patients with GCA who received secukinumab at 14 Italian centers with at least six months of follow‐up.
Luca Iorio   +28 more
wiley   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

open access: yesInternational Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam   +2 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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