Results 161 to 170 of about 4,026,358 (295)

Validation of Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric Measures for Children With Chronic Nonbacterial Osteomyelitis

open access: yesArthritis Care &Research, EarlyView.
Objective To assess the validity of the Patient‐Reported Outcomes Measurement Information System (PROMIS) Pediatric measures in patients with chronic nonbacterial osteomyelitis (CNO). Methods Within the longitudinal patient registry of CNO, English‐speaking patients aged 8 years and older self‐reported PROMIS Pediatric measures of fatigue, pain ...
Mary M. Eckert   +43 more
wiley   +1 more source

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

open access: yesArthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling   +4 more
wiley   +1 more source

Innovation, Growth and Convergence in the Euro-Mediterranean Area: Implications for MENA Countries [PDF]

open access: yes
This paper focuses on the innovation gap between countries in the Euro-Mediterranean (Euromed) area and its implications in terms of growth and convergence.
Nicolas Péridy
core  

Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns

open access: yesArthritis Care &Research, Accepted Article.
Objective Rheumatoid arthritis is a heterogeneous disease. Data‐driven approaches, from synovial histology to joint involvement patterns (JIPs), have sought to define clinically meaningful subgroups. Whether these subgroups represent stable phenotypes or transient disease states remains unclear.
Tjardo Maarseveen   +24 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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