Results 221 to 230 of about 5,783,966 (296)

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

Artificial Intelligence for Improving the Management of People With Epilepsy in Low-and-Middle Income Countries. [PDF]

Eur J Neurol
Ryvlin P, Beniczky S, Aurlien H, Bernini A, Jones GD, Kariuki SM, Spahr A, Tveit J, Sen A.   +8 more
europepmc   +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

Comment on "The Psychometric Properties of the Caregiver Feeding Style Questionnaire: A Cross-Cultural Validation in Spanish Parents". [PDF]

Res Nurs Health
Kumar S, Gupta N, Singh SK, Srinivasan H, Vadhithala V.   +4 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

Retinal Vascularity Index in Mild Cognitive Impairment. [PDF]

Transl Vis Sci Technol
D'Cunha R, Hsu J, Melcher J, Zhu M, Choi A, Haystead A, Sharma A, Hudlikar A, Song R, Ng H, Stinnett S, Agrawal R, Johnson KG, Grewal DS, Fekrat S.   +14 more
europepmc   +1 more source

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +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

An Interpretable Center-Specific Machine Learning Model for Risk Stratification Following Mitral Valve Surgery: A Pilot Study. [PDF]

J Clin Med
Stańska A, Kilarska M, Janeczek M, Karolak W, Klapkowski A.   +4 more
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source