Results 141 to 150 of about 10,209,746 (308)

Estimating the Prevalence and Incidence of Symptomatic Hand Osteoarthritis in the Netherlands Using Primary Care Electronic Health Records

Arthritis Care &Research, EarlyView.
Objective Estimating the incidence and prevalence of symptomatic hand osteoarthritis (OA) in the Dutch population using a validated algorithm that integrates free‐text data from primary care electronic health records (EHRs). Methods This retrospective cohort study used the Integrated Primary Care Information database, including EHRs from approximately ...
Onur Kaya, Jacoline van den Driest, Laura Struik, Margreet Kloppenburg, Ruud Selles, Daniel Prieto Alhambra, Sita Bierma‐Zeinstra, Dieuwke Schiphof   +7 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

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

Attofarad-Class Ultra-High-Capacitance Resolution Capacitive Readout Circuits

Sensors
In order to meet the application requirements for high-precision and low-noise accelerometers in micro-vibration measurement and navigation fields, this paper presents the design and testing of an ultra-high-capacitance resolution capacitive readout ...
Guoteng Ren, Saifei Yuan, Jingjing Peng, Ruitao Liu, Yuhao Feng, Haonan Liu, Wenshuai Lu, Fei Xing, Ting Sun, Shijie Yu   +9 more
doaj   +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

A Wide Tuning Range and Low Phase Noise VCO using New Capacitor Bank Structure

Majlesi Journal of Electrical Engineering
This paper presents a wide tuning range, and low noise voltage controlled oscillator (VCO) based on cross-coupled and colpitts structures. The advantages of this work provide a low-phase noise and robust start-up condition, leading to minimized the dc ...
Mostafa Katebi, Abbas Nasri, Siroos Toofan   +2 more
doaj  

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

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