Results 171 to 180 of about 698,300 (306)
Objective Cam morphology, which is a significant risk factor for hip osteoarthritis, is commonly quantified by the alpha angle (AA). This study aims to explore the potential of the triangular index ratio (TIR) to quantify cam morphology on anteroposterior radiographs by assessing the association between TIR‐defined cam morphology and the development of
Jinchi Tang +7 more
wiley +1 more source
A Heavy Tailed Expectation Maximization Hidden Markov Random Field Model with Applications to Segmentation of MRI. [PDF]
Castillo-Barnes D +7 more
europepmc +1 more source
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos +2 more
wiley +1 more source
PReFerSim: fast simulation of demography and selection under the Poisson Random Field model. [PDF]
Ortega-Del Vecchyo D +2 more
europepmc +1 more source
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
A Neural Conditional Random Field Model Using Deep Features and Learnable Functions for End-to-End MRI Prostate Zonal Segmentation. [PDF]
Hung ALY +7 more
europepmc +1 more source
Fluorescence microscopy image noise reduction using a stochastically-connected random field model. [PDF]
Haider SA +7 more
europepmc +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
Structure-based Markov random field model for representing evolutionary constraints on functional sites. [PDF]
Jeong CS, Kim D.
europepmc +1 more source

