Results 111 to 120 of about 24,713,244 (334)
Multi-Output Gaussian Processes for Crowdsourced Traffic Data Imputation
Traffic speed data imputation is a fundamental challenge for data-driven transport analysis. In recent years, with the ubiquity of GPS-enabled devices and the widespread use of crowdsourcing alternatives for the collection of traffic data, transportation
Henrickson, Kristian +2 more
core +1 more source
Objective Pulmonary fibrosis (PF) is a severe extra‐articular manifestation of rheumatoid arthritis (RA). This study aimed to externally validate a genetic risk score (GRS) and a combined risk score (CRS) for predicting the risk of RA‐associated PF in an independent cohort of patients with early RA.
Mikael Brink +3 more
wiley +1 more source
This study highlights the impact of missing data imputation techniques in failure prediction. Existing studies have focused less on the issue of missing data, examined less the overall performance of the imputation techniques, and often concentrated on ...
Kaoutar El Madou +2 more
doaj +1 more source
Multivariate Data Imputation using Trees [PDF]
We address the problem of completing two files with records containing a fully observed common subset of variables. The tecnique investigated involves the use of regression and/or classification trees.
Bárcena Ruiz, María Jesús +1 more
core
Sex Differences in Medication Discontinuation in Axial Spondyloarthritis
Objective We examined sex differences in medication discontinuation among patients with axial spondyloarthritis (axSpA) initiating tumor necrosis factor inhibitors (TNFi), interleukin‐17 inhibitors (IL‐17i), or JAK inhibitors (JAKi). Methods Using data from the Rheumatology Informatics System for Effectiveness (RISE) Registry (2003–2025), we assessed ...
Rachael Stovall +9 more
wiley +1 more source
Evaluating Performance of Missing Data Imputation Methods in IRT Analyses
Missing data is a common problem in datasets thatare obtained by administration of educational and psychological tests. It is widelyknown that existence of missing observations in data can lead to serious problemssuch as biased parameter estimates and ...
Ömür Kaya Kalkan +2 more
doaj +1 more source
BACKGROUND: Net survival is the survival probability we would observe if the disease under study were the only cause of death. When estimated from routinely collected population-based cancer registry data, this indicator is a key metric for cancer ...
Carpenter, James R +3 more
core +1 more source
Objective The purpose was to evaluate a biomarker score consisting of MUC5B rs35705950 promoter variant, plasma matrix metalloproteinase‐7 (MMP‐7), and serum anti–malondialdehyde‐acetaldehyde (anti‐MAA) antibody for rheumatoid arthritis (RA)–associated interstitial lung disease (ILD) risk stratification.
Kelsey Coziahr +16 more
wiley +1 more source
Taking "Don't Knows" as Valid Responses: A Complete Random Imputation of Missing Data [PDF]
Incomplete data is a common problem of survey research. Recent work on multiple imputation techniques has increased analysts' awareness of the biasing effects of missing data and has also provided a convenient solution.
Martin Kroh
core
Objective We investigated whether a diagnosis of rheumatoid arthritis (RA) affects the quality of inpatient acute myocardial infarction (AMI) care and long‐term mortality post‐AMI. Methods We analyzed data from 784,091 adults, 6,047 with a diagnosis of RA, from England and Wales hospitalized with AMI between 2005 and 2019 from the Myocardial Ischaemia ...
Megan Butler +8 more
wiley +1 more source

