From prediction to advising: a multi model approach using NBME subject examinations to inform step 2 CK performance. [PDF]
Boateng B +5 more
europepmc +1 more source
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
Inferring effective neuronal circuits via network flux counting. [PDF]
Chen KS, Yang YJ.
europepmc +1 more source
Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns
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
Capturing Heterogeneous Time-Variation in Covariate Effects in Non-Proportional Hazard Regression Models. [PDF]
Hagemann N, Kneib T, Möllenhoff K.
europepmc +1 more source
Positive Affect is Associated with Better Physical Function in Early Rheumatoid Arthritis
Objective This study examined the association between positive affect and physical function in individuals with early rheumatoid arthritis (RA). Methods We analyzed baseline data from 129 adults with early RA (persistent joint symptoms for ≤ 24 months) and active disease enrolled in the Central Pain in RA 2 (CPIRA‐2) study.
Burcu Aydemir +9 more
wiley +1 more source
The Variances of Regression Coefficient Estimates Using Aggregate Data [PDF]
This paper considers the effect of aggregation on the variance of parameter estimates for a linear regression model with random coefficients and an additive error term.
Roy E. Welsch, Edwin Kuh
core
Infant mortality across EU health systems: heterogeneity encoding, fixed effects regression, and machine learning in a small macro panel. [PDF]
Kisa E, Kisa A.
europepmc +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
Integrating Meta-Analysis Into a Specific Study (InMASS) for Estimating the Target-Population Average Treatment Effect. [PDF]
Hanada K, Kojima M.
europepmc +1 more source

