Results 91 to 100 of about 263,880 (288)
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah +5 more
wiley +1 more source
Objective In complex diseases, it is challenging to assess a patient's disease state, trajectory, treatment exposures, and risk of multiple outcomes simultaneously, efficiently, and at the point of care. Methods We developed an interactive patient‐level data visualization and analysis tool (VAT) that automates illustration of the trajectory of a ...
Ji Soo Kim +18 more
wiley +1 more source
Transition-age youth exiting foster care (TAY) are at high risk for housing instability, with nearly half experiencing homelessness before age 26. Multi-level factors are associated with greater risk, including individual, social, and geographic contexts.
Sarah Carter Narendorf +3 more
doaj +1 more source
Objective A leading cause of death among patients with scleroderma (SSc), interstitial lung disease (ILD) remains challenging to prognosticate. The discovery of biomarkers that accurately determine which patients would benefit from close monitoring and aggressive therapy would be an essential clinical tool.
Cristina M. Padilla +13 more
wiley +1 more source
Objective We aimed to identify unique disease trajectories within rheumatoid arthritis–associated interstitial lung disease (RA‐ILD) based on longitudinal forced vital capacity (FVC) values and their associated clinical outcomes. Methods We performed a cohort study of RA‐ILD within the Veterans Health Administration from 1999 to 2021.
Bryant R. England +9 more
wiley +1 more source

