Results 171 to 180 of about 3,054,349 (257)
Functional Approximation Methods for Differentially Private Distribution Estimation. [PDF]
Tao Y, Sarwate AD.
europepmc +1 more source
Objectives This study aimed to determine whether gout flare resolution is associated with physical activity and sleep. These findings were intended to inform the future development of a definition for flare resolution. Methods Data from 81 participants with gout who experienced >1 flare during a 6‐month prospective observational study were included ...
Sarah Stewart +12 more
wiley +1 more source
Generative AI in clinical practice: how should rheumatologists evaluate and monitor emerging tools?
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
Structured low-rank approximation with missing data
The approach of SIAM J. Matrix Anal. Appl., 26(4):1083--1099 for solving structured total least squares problems is generalized to weighted structured low-rank approximation with missing data. The method proposed is based on elimination of the correction
Markovsky, Ivan, Usevich, Konstantin
core +1 more source
Approximating prediction error variances and reliabilities in a multiple-trait genomic prediction model using Monte Carlo sampling. [PDF]
Heikkilä A +4 more
europepmc +1 more source
Objectives This study synthesised the content and reporting completeness of published physical therapist‐led interventions for glenohumeral osteoarthritis (GHOA). Methods This systematic review undertook electronic database searches in PubMed, EMBASE, Cochrane, CINAHL and PEDro (until June 2025) for any peer‐reviewed articles/studies describing ...
Daha G Muhammad +5 more
wiley +1 more source
HLR-UFS: Hessian-based Unsupervised Feature Selection using Low-Rank Approximation. [PDF]
Zhang J, Lin W, Liu Y, Tu S, Peng M.
europepmc +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
Robust Augmented-Diffusion Filtered-x Maximum Correntropy Criterion for Distributed Active Noise Control Under Impulsive Noise. [PDF]
Peng D, He Y, Liu Q.
europepmc +1 more source

