Results 171 to 180 of about 128,496 (265)

Longitudinal Changes in Adiposity After a Youth Sport‐Related Knee Injury: Informing Posttraumatic Osteoarthritis Prevention

open access: yesArthritis Care &Research, EarlyView.
Objective Youth who experience a sport‐related knee injury have elevated odds of becoming overweight or developing obesity in 3 to 10 years, compounding their risk for posttraumatic osteoarthritis (PTOA). To inform prevention strategies, this study compared patterns of adiposity change between youth with a sport‐related knee injury and uninjured youth ...
Justin M. Losciale   +6 more
wiley   +1 more source

Utilization of Recycled Brick Aggregate in Cementitious Composites: Mechanical Performance, Cement Matrix Solidification Effect and Life Cycle Assessment. [PDF]

open access: yesMaterials (Basel)
Václavík V   +9 more
europepmc   +1 more source

Generative AI Utilization and Perspectives Among Reproductive‐Age Women with Systemic Autoimmune and Rheumatic Diseases

open access: yesArthritis Care &Research, Accepted Article.
Objective Reproductive‐age women with systemic autoimmune and rheumatic diseases (SARDs) have unique information needs related to their SARDs and reproductive health. We sought to understand their use of and receptivity to current and hypothetical generative artificial intelligence (AI) tools for health information‐seeking. Methods We conducted a cross‐
Mariam Arif   +5 more
wiley   +1 more source

Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns

open access: yesArthritis Care &Research, Accepted Article.
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

dynoGP: Deep Gaussian Processes for Dynamic System Identification

open access: yesInternational 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   +3 more
wiley   +1 more source

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