Results 191 to 200 of about 20,375,797 (310)

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

Arthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling, Ties van het Erve, Yvette van de Berg, Simon Mastbergen, Julia Spierings   +4 more
wiley   +1 more source

Diseño de espacios académicos B-learning (Electiva)

La electiva Diseño de espacios académicos b-learning, brinda las herramientas necesarias para construir paso a paso espacios académicos en modalidad b-learning siguiendo las características del enfoque de formación Lasallista.
Betancur Chicué, Viviana
core  

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

Targeted Active Learning for Bayesian Decision-Making

Active learning is usually applied to acquire labels of informative data points in supervised learning, to maximize accuracy in a sample-efficient way.
Kaski, Samuel, Tiulpin, Aleksei, Filstroff, Louis, Sundin, Iiris, Kylmäoja, Juuso, Mikkola, Petrus   +5 more
core  

Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns

Arthritis Care &Research, Accepted Article.
Objective Rheumatoid arthritis is a heterogeneous disease. Data‐driven approaches, from synovial histology to joint involvement patterns (JIPs), have sought to define clinically meaningful subgroups. Whether these subgroups represent stable phenotypes or transient disease states remains unclear.
Tjardo Maarseveen, Yasuo Nagafuchi, Kristina Lend, Seyam Alemyar, Herman Kasper Glas, Gerdur Gröndal, Bjorn Gudbjornsson, Espen A. Haavardsholm, Kim Hørslev Petersen, Jon Lampa, Merete Lund Hetland, Dan Nordström, Mike Nurmohamed, Mikkel Østergaard, Anna Rudin, Marte Schrumpf Heiberg, Tuulikki Sokka‐Isler, Till Uhlig, Josien Veris‐van Dieren, Ronald van Vollenhoven, Tom Huizinga, Marcel JT Reinders, Sytske Anne Bergstra, Erik van den Akker, Rachel Knevel   +24 more
wiley   +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

In-memory phononic learning toward cognitive mechanical intelligence. [PDF]

Sci Adv
Zhang Y, Wang KW.
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

ManyBabies 3: A Multi-Lab Study of Infant Algebraic Rule Learning. [PDF]

Dev Sci
Visser I, Geambasu A, Kachergis G, Oliveira CM, Rocha-Hidalgo J, Zettersten M, Ahamat T, Alessandroni N, Althaus N, Arunachalam S, Aussems S, Axelsson EL, Aydin Z, Baumgartner HA, Bergmann C, Bettoni R, Black AK, Bulf H, Byers-Heinlein K, Capparini C, Carroll L, Carstensen A, Cebulla R, Chen X, Chládková K, Colavolpe B, Constantine RR, Cortes EE, Doyle FL, Exner A, Forbes SH, Franchin L, Geraci A, Gervain J, Gonzalez-Gomez N, Hagelund S, Hannon EE, Havron N, Jaffe-Dax S, Johnson SP, Jędryczka W, Kartushina N, Struhl MK, Koleini A, Kona A, Kong SP, Kosie JE, Kuc̆erová M, Cook K, Leslie JW, Lew-Williams C, Li SWY, Livne R, Marklund E, Mayor J, Misiak M, Moreau D, Mueller JL, Muhinyi A, Quinn AA, Raijmakers MEJ, Rosslund A, Schwarz IC, Shinskey JL, Shukla M, Sirois S, Sorokowski P, Sowan B, Tauzin T, Tsui ASM, Turconi M, Urizar RC, Wagner L, Wermelinger S, Westermann G, Weyers I, Yuan LSB, Zaharieva MS, Zamuner TS, Zapiór B, Zasso S, Zhou JG, Soderstrom M, Levelt CC.   +83 more
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source