Results 171 to 180 of about 8,032,770 (318)

Digital Behavioral Therapy Improves Outcome in Patients With Axial Spondyloarthritis and Persistent Pain: A Randomized Controlled Trial

open access: yesArthritis Care &Research, EarlyView.
Objective Axial spondyloarthritis (axSpA) is often associated with persistent pain despite effective anti‐inflammatory treatment. Digital health applications (DHAs) provide innovative approaches to address multidimensional aspects of persistent pain through psychological and behavioral strategies. The aim of this study was to assess the impact of a DHA
David Kiefer   +7 more
wiley   +1 more source

A Qualitative Analysis of Patient Perspectives and Preferences in Lupus Management to Guide Lupus Guidelines Development

open access: yesArthritis Care &Research, EarlyView.
Objective A patient‐centered approach for chronic disease management, including systemic lupus erythematosus (SLE), aligns treatment with patients’ values and preferences, leading to improved outcomes. This paper summarizes how patient experiences, perspectives, and priorities informed the American College of Rheumatology (ACR) 2024 Lupus Nephritis (LN)
Shivani Garg   +20 more
wiley   +1 more source

Healthcare outcomes and special education eligibility in children with congenital CMV. [PDF]

open access: yesPLoS One
Rochat R   +4 more
europepmc   +1 more source

Optimized Time–Frequency Analysis for Induction Motor Fault Detection Using Hybrid Differential Evolution and Deep Learning Techniques

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
Workflow of the parameter optimization process for ITSC fault detection, applying Differential Evolution optimization and the Smooth Pseudo Wigner‐Ville Distribution for signal processing. The optimized parameters are then used in the failure identification pipeline, which combines the signal processing with a YOLO‐based architecture for fault severity
Rafael Martini Silva   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy