Results 111 to 120 of about 345,922 (215)
Objective This study aimed to characterize cannabis product choices (cannabinoid content and formulation) among patients with rheumatologic conditions and their associations with patient factors, patient‐reported perceived side effects, and positive impacts.
Susan Zhang +10 more
wiley +1 more source
Objective This study aims to investigate lifestyle‐related factors in patients with psoriatic arthritis (PsA) and their association with disease activity measurements. Methods This multicenter cohort included 938 patients who were newly diagnosed with PsA between 2013 and 2023.
Batoul Hojeij +11 more
wiley +1 more source
The Lupus Damage Index Revision Program: Results From the Item Generation and Reduction Phases
Objective A data‐driven and expert/patient consensus‐based project to develop a revised Systemic Lupus International Collaborating Clinics (SLICC)/American College of Rheumatology (ACR) Damage Index (SDI) is under way supported by SLICC, ACR, and the Lupus Foundation of America. Our objective is to report the item generation and reduction phase results
Burak Kundakci +25 more
wiley +1 more source
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
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
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
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Thermomechanical fatigue tests of laser beam powder bed fusion (PBF‐LB) Inconel 718 show that the additively manufactured material reaches almost the lifetimes of conventionally‐rolled material under no‐dwell conditions. Introducing dwell times at the maximum temperature markedly reduces the lifetimes due to pronounced grain boundary sliding associated
Stefan Guth +6 more
wiley +1 more source

