Results 131 to 140 of about 248,303 (301)
Task-Aligned Transformer Imputation for Long-Horizon Air Quality Forecasting
Accurate long-horizon air-quality forecasting becomes difficult when historical observations are missing or irregularly sampled because reconstruction errors can propagate into downstream predictions.
Grega Vrbančič +2 more
doaj +1 more source
Objective This study investigated the association between frailty and cancer incidence and mortality in patients with rheumatoid arthritis (RA). It aimed to identify how frailty influences cancer risk and cancer‐specific outcomes. Methods This retrospective cohort study analyzed data from the Veterans’ Affairs Rheumatoid Arthritis Registry (2002–2023).
Bhavik Bansal +12 more
wiley +1 more source
Aerosol Optical Depth (AOD) is a crucial parameter for monitoring air quality and studying atmosphere behavior, but satellite-based AOD measurements often suffer from significant gaps due to cloud cover and other obstructions.
Anusha Srirenganathan Malarvizhi +4 more
doaj +1 more source
Objective We describe the frequency, risk factors, severity, and management of actionable and serious adverse events (AAE and SAE) in children with newly diagnosed Juvenile Idiopathic Arthritis (JIA) in Canada. Methods We enrolled patients within 3 months of JIA diagnosis in the Canadian Alliance of Pediatric Rheumatology Investigators (CAPRI) Registry,
Bashayer Alnuaimi +10 more
wiley +1 more source
Objective The objective of this study was to evaluate the real‐world effectiveness and safety of secukinumab in patients with giant cell arteritis (GCA). Methods This multicenter retrospective study included patients with GCA who received secukinumab at 14 Italian centers with at least six months of follow‐up.
Luca Iorio +28 more
wiley +1 more source
Missing data are a persistent challenge in large healthcare datasets, often undermining both statistical validity and machine learning performance when handled using simplistic assumptions. In this work, we examine how entropy-based diagnostics can guide
Deepa Fernandes Prabhu +2 more
doaj +1 more source
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 +10 more
wiley +1 more source
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
Data‐Driven Materials Science for Energy‐Sustainable Applications
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley +1 more source
MANOVA modelling of a chiropractic longitudinal study using multiple imputation [PDF]
The purpose of this report is to present the detailed statistical analysis of a randomised, placebo-controlled trial comparing two different treatment modalities to an intervention of no known benefit for people with acute or subacute thoracic spine pain.
Clarke, B.R., Bowden, R.S., Walker, B.F.
core

