Results 91 to 100 of about 409,869 (257)
Spreading Dynamics of Capital Flow Transfer in Complex Financial Networks. [PDF]
Entropy (Basel), 2023 Peng W, Chen T, Zheng B, Jiang X.
europepmc +1 more source
Systemic cascades on inhomogeneous random financial networks. [PDF]
Math Financ Econ, 2023 Hurd TR.
europepmc +1 more source
Arthritis Care &Research, EarlyView.Over the past 50 years, the science of pediatric rheumatology has grown exponentially due to an expansion in the understanding of complex rheumatic conditions and a surge in novel targeted therapeutics. Physician‐scientists in the field of pediatric rheumatology have played major roles in these advancements that have improved the care of children ...
Ekemini A. Ogbu +2 more
wiley +1 more source
Learning Financial Networks with High-frequency Trade Data. [PDF]
Data Sci Sci, 2023 Karpman K, Basu S, Easley D, Kim S.
europepmc +1 more source
Arthritis Care &Research, EarlyView.Objective This study aimed to describe real‐world trends in preconception and prenatal use of antirheumatic drugs among pregnant individuals with rheumatic diseases in Ontario, Canada. Methods We conducted a time‐series analysis using repeated cross‐sectional data to examine annual patterns of disease‐modifying antirheumatic drug (DMARD) use among ...
Shenthuraan Tharmarajah +6 more
wiley +1 more source
Quantum computing reduces systemic risk in financial networks. [PDF]
Sci Rep, 2023 Aboussalah AM, Chi C, Lee CG.
europepmc +1 more source
Arthritis Care &Research, Accepted Article.Objectives We aimed to determine whether the short‐term response to biologics in biologic‐naïve psoriatic arthritis (PsA) is better in patients initiating biologic treatment early in the disease course. Methods PsA patients who started biologic therapy from the year 2000 to 2025 were included for analysis. Patients considered in the early treatment (ET)
Sung Min Cho +4 more
wiley +1 more source
Measure cross-sectoral structural similarities from financial networks. [PDF]
Sci Rep, 2023 Boersma M +4 more
europepmc +1 more source
Arthritis Care &Research, Accepted Article.Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein +3 more
wiley +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International 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 +2 more
wiley +1 more source