Results 121 to 130 of about 3,370,652 (304)
Discordance Between Patient and Physician Global Assessments in Early Systemic Sclerosis
Objective This study aims to identify factors associated with patient global assessment (PtGA) and physician global assessment (PhGA) and discordance between them in systemic sclerosis (SSc). Methods Data from adults with early SSc (<5 years) from the Collaborative National Quality and Efficacy Registry were included.
Ellen Romich +35 more
wiley +1 more source
The package dcemriS4 provides a complete set of data analysis tools for quantitative assessment of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).
Whitcher, B., Schmid, V.J.
core +1 more source
The Gut–Heart Axis in Systemic Sclerosis: Evidence From a Large Prospective Early Disease Cohort
Objective Cardiac involvement significantly impacts prognosis in systemic sclerosis (SSc), highlighting the need for early risk stratification. Gastrointestinal (GI) symptoms are common and often manifest early. Emerging data suggest a link between GI and cardiac manifestations, possibly through shared mechanisms like dysautonomia.
Francesca R. Di Ciommo +9 more
wiley +1 more source
To investigate the relationship between clinical stages and apparent diffusion coefficient (ADC) changes in the brain of patients with subacute sclerosing panencephalitis (SSPE).
Alkan, Alpay +6 more
core +1 more source
Objective Gastrointestinal (GI) involvement can lead to malnutrition in patients with systemic sclerosis (SSc). Body mass index (BMI) remains the most widely used marker to screen nutritional status. We aimed to identify predictors of lower BMI in patients with SSc. Methods Patients with SSc from a prospective US cohort meeting 2013 American College of
Ali Y. Ayla +8 more
wiley +1 more source
To determine the potential benefit of combined respiratory-cardiac triggering for diffusion-weighted imaging (DWI) of kidneys compared to respiratory triggering alone (RT)
Thoeny, Harriet C +11 more
core +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
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
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Stability effects on results of diffusion tensor imaging analysis by reduction of the number of gradient directions due to motion artifacts: an application to presymptomatic Huntington's disease. [PDF]
In diffusion tensor imaging (DTI), an improvement in the signal-to-noise ratio (SNR) of the fractional anisotropy (FA) maps can be obtained when the number of recorded gradient directions (GD) is increased.
Müller, HP +6 more
core
Geometry‐driven thermal behavior in wire‐arc additive manufacturing (WAAM) influences microstructural evolution during nonequilibrium solidification of a chemically complex Fe–Cr–Nb–W–Mo–C nanocomposite system. By comparing different deposits configurations, distinct entropy–cooling rate correlations, segregation, and carbide evolution are revealed ...
Blanca Palacios +5 more
wiley +1 more source

