Results 151 to 160 of about 709,384 (266)

Muscle Strength and Power Improve Despite Small Increase in Quadriceps Cross-Sectional Area in Massive Knee Joint Destruction: A Two-Year Follow-Up Case Report. [PDF]

Muscles
Cruz-Montecinos C, Núñez-Cortés R, Becerra-Yañez P, Oyarzún A, Calatayud J.   +4 more
europepmc   +1 more source

Generative Artificial Intelligence Utilization and Perspectives Among Reproductive‐Age Women With Systemic Autoimmune and Rheumatic Diseases

Arthritis Care &Research, EarlyView.
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, Catherine Wright, Samantha Rodriguez, Sarah Graves, Tamar Krishnamurti, Mehret Birru Talabi   +5 more
wiley   +1 more source

Association of iliopsoas muscle cross-sectional area with postoperative complications in older lung cancer patients: a retrospective study. [PDF]

J Cardiothorac Surg
Kubota S, Samejima J, Koike Y, Tada M, Miyoshi T, Tane K, Wakabayashi M, Aokage K, Tsuboi M.   +8 more
europepmc   +1 more source

Unsupervised Machine Learning Identifies Shared Biomechanical and Clinical Variation in Individuals with Knee Osteoarthritis and High BMI: A Secondary Analysis of the IDEA Trial

Arthritis Care &Research, Accepted Article.
Objective High body mass index (BMI≥27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck, J. Elyse Borgert, Hyeon Lee, Liubov Arbeeva, Yvonne M. Golightly, Richard F. Loeser, Leigh F. Callahan, Stephen P. Messier, Brian Pietrosimone, Amanda E. Nelson, James S. Marron   +10 more
wiley   +1 more source

Computed tomography-based analysis of external jugular vein cross-sectional area for vascular access in cats. [PDF]

Front Vet Sci
Seo D, Hong S, Kim MS, Oh T.
europepmc   +1 more source

Generative AI in clinical practice: how should rheumatologists evaluate and monitor emerging tools?

Arthritis Care &Research, Accepted Article.
Generative artificial intelligence (AI) is increasingly being used in rheumatology practice, to assist with tasks such as documentation, record summarization, and clinical decision support. Rheumatologists need a practical approach to determining what evidence and oversight each application requires.
Koushan Kouranloo, Mrinalini Dey, Jinoos Yazdany   +2 more
wiley   +1 more source

Ultrasound-Based Severity Stratification in Carpal Tunnel Syndrome: Median Nerve Cross-Sectional Area for Distinguishing Severe from Moderate Disease. [PDF]

Diagnostics (Basel)
Peker I, Alaamel A, Cengiz N.
europepmc   +1 more source

The content and reporting completeness of physical therapist‐led interventions for glenohumeral osteoarthritis: a systematic review

Arthritis Care &Research, Accepted Article.
Objectives This study synthesised the content and reporting completeness of published physical therapist‐led interventions for glenohumeral osteoarthritis (GHOA). Methods This systematic review undertook electronic database searches in PubMed, EMBASE, Cochrane, CINAHL and PEDro (until June 2025) for any peer‐reviewed articles/studies describing ...
Daha G Muhammad, Nadine E Foster, Mickylle Pelaez, Karina O'Leary, Ilana N Ackerman, Jonathan G Quicke   +5 more
wiley   +1 more source

Decreased Thigh Muscle Cross-Sectional Area Following Anterior Cruciate Ligament Injury Depends on Concomitant Meniscal Injury and Subject Sex. [PDF]

J Orthop Res
French K, Toth MJ, Fiorentino N, Vacek P, DeSarno M, Tourville TW, Failla M, Geeslin A, Geeslin M, Gardner-Morse M, Parkinson P, Beynnon B.   +11 more
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International 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, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source