Results 81 to 90 of about 314,456 (263)

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source

Generative AI Utilization and Perspectives Among Reproductive‐Age Women with Systemic Autoimmune and Rheumatic Diseases

Arthritis Care &Research, Accepted Article.
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

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

Implementing a Functional Group Analysis Activity to Support Student Learning in Medicinal Chemistry: A Three-Year Experience

Pharmacy
Many pharmacy students begin medicinal chemistry with limited experience in chemical structure interpretation and reactivity patterns, making it difficult to connect foundational concepts to real-world drug behavior. We introduced a low-stakes functional
Ansel Belani, Jitendra D. Belani
doaj   +1 more source

Effect Modification of Cigarette Smoking on the Relationship between Post‐traumatic Stress Disorder, Other Mental Health Conditions and Rheumatoid Arthritis Risk: A Large Case‐Control Study in U.S. Veterans

Arthritis Care &Research, Accepted Article.
Objective We examined associations of post‐traumatic stress disorder (PTSD) and other mental health disorders (OMH) with rheumatoid arthritis (RA), accounting for effects of smoking. Methods We conducted a matched case‐control study, identifying incident RA cases and controls using national Veteran Health Administration data (2006‐2019).
Kelsey Coziahr, Harlan Sayles, Tate M. Johnson, Joshua F. Baker, Punyasha Roul, Grant W. Cannon, Gary A. Kunkel, Katherine D. Wysham, Gail S. Kerr, Amir A. Razmjou, Isaac Smith, Jennifer L. Barton, Maria I. Danila, Jonathan S. Richards, Bryant R. England, Ted R. Mikuls   +15 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

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

An Experimental Survey of Incremental Transfer Learning for Multicenter Collaboration

IEEE Access
Due to data privacy constraints, data sharing among multiple clinical centers is restricted, which impedes the development of high performance deep learning models from multicenter collaboration.
Yixing Huang, Christoph Bert, Ahmed Gomaa, Rainer Fietkau, Andreas Maier, Florian Putz   +5 more
doaj   +1 more source

Incorporation of peer learning in first MBBS curriculum to enhance metacognition skills [PDF]

Al Ameen Journal of Medical Sciences, 2012
Peer learning can be incorporated in the first MBBS curriculum along with didactic lectures and tutorials. Peer learning is when a student learns from another student who has been trained to explain the topic and discuss it. Peer learning improves domain-
Manas Kanti Ray, Suranjana Ray
doaj  

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