Results 231 to 240 of about 520,796 (299)
Exploring antecedents and consequences of value co-creation of women entrepreneurs: a conceptual framework and research agenda. [PDF]
Hassan B, Mohamad B.
europepmc +1 more source
Objective We describe the frequency, risk factors, severity, and management of actionable and serious adverse events (AAE and SAE) in children with newly diagnosed Juvenile Idiopathic Arthritis (JIA) in Canada. Methods We enrolled patients within 3 months of JIA diagnosis in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry,
Bashayer Alnuaimi +10 more
wiley +1 more source
Coupling with opinion dynamics promotes prosocial behavior in multilayer networks. [PDF]
Bhaumik J, Masuda N.
europepmc +1 more source
Objective The goal of this study was to determine if patient global assessment (PGA) scores reported by patients with axial spondyloarthritis (AxSpA) before the development of the AxSpA Disease Activity Score (ASDAS) can be used as a substitute for the global item of the ASDAS formula.
Connor Vershel +8 more
wiley +1 more source
Social Anxiety Modulates Default Mode Network Dysfunction and Working Memory Impairment During Social Media-Like Cue Distraction. [PDF]
Hu Y, Wei Z, Xu L, Becker B, Kou J.
europepmc +1 more source
Objective Existing patient‐reported outcome (PRO) measures for systemic sclerosis (SSc) have important limitations, including inadequate coverage of early disease and limited inclusion of diffuse cutaneous (dcSSc) and limited cutaneous (lcSSc) subtypes.
George J. Greene +5 more
wiley +1 more source
Generative artificial intelligence (AI) is increasingly being used in rheumatology practice, to assist with tasks such as documentation, record summarization, and clinical decision support. Rheumatologists need a practical approach to determining what evidence and oversight each application requires.
Koushan Kouranloo +2 more
wiley +1 more source
Large-Scale Cerebellar-Cerebral Network Alterations Underlying Impaired Social Predictive Processing in Cerebellar Neurodegeneration. [PDF]
Siciliano L +11 more
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
Perceptions of homogeneity reproduction in health sciences academia. [PDF]
Buckup R +3 more
europepmc +1 more source

