Results 101 to 110 of about 175,631 (262)

Comparison of different approaches in handling missing data in longitudinal multiple-item patient-reported outcomes: a simulation study

Health and Quality of Life Outcomes
Background Patient-reported outcomes (PROs) are important clinical outcomes widely used as primary and secondary endpoints in clinical studies. However, PRO data often suffers from missing values for various reasons, which pose challenges to data ...
Minqian Yan, Lizhi Zhou, Chongye Zhao, Chen Shi, Chunquan Ou   +4 more
doaj   +1 more source

Associations of Frailty With the Risk of Incident Cancer and Cancer‐Related Mortality in Veterans With Rheumatoid Arthritis

Arthritis Care &Research, EarlyView.
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, Aaron Baraff, Katherine Wysham, James S. Andrews, Bryant R. England, Ted R. Mikuls, Joshua Baker, Kaleb Michaud, Alexa Meara, Una Makris, Carolyn Presley, Ariela Orkaby, Namrata Singh   +12 more
wiley   +1 more source

Incidence, Risk Factors and Management of Adverse Events in Contemporary Real‐World Care of Children with Juvenile Idiopathic Arthritis

Arthritis Care &Research, Accepted Article.
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, Roberta A. Berard, Jean‐Philippe Proulx‐Gauthier, Heinrike Schmeling, Michelle Batthish, Gilles Boire, Adam M. Huber, Dax G. Rumsey, Jaime Guzman, Gaëlle Chédeville, The CAPRI registry Investigators   +10 more
wiley   +1 more source

Missing data imputation, prediction, and feature selection in diagnosis of vaginal prolapse. [PDF]

BMC Med Res Methodol, 2023
Fan M, Peng X, Niu X, Cui T, He Q.
europepmc   +1 more source

Real‐World Effectiveness and Safety of Secukinumab in Giant Cell Arteritis: An Italian Multicenter Cohort Study

Arthritis Care &Research, EarlyView.
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, Federica Davanzo, Caterina Ricordi, Milena Bond, Ruggiero Mascolo, Jacopo Mora, Alessandro Tomelleri, Angelo Fassio, Francesca Cuzzocrea, Sara Monti, Edoardo Conticini, Fabiola Atzeni, Paolo Delvino, Carlotta Nannini, Augusta Ortolan, Francesco Pollastri, Ester Vivaldelli, Chiara Marvisi, Paola Toniati, Antonio Brucato, Alessandra Milanesi, Francesca Regola, Enrico Tombetti, Lorenzo Dagna, Roberta Ramonda, Christian Dejaco, Luca Quartuccio, Carlo Salvarani, Roberto Padoan   +28 more
wiley   +1 more source

A Hybrid Missing Data Imputation Method for Batch Process Monitoring Dataset. [PDF]

Sensors (Basel), 2023
Gan Q, Gong L, Hu D, Jiang Y, Ding X.
europepmc   +1 more source

gcimpute: A Package for Missing Data Imputation

Journal of Statistical Software
This article introduces the Python package gcimpute for missing data imputation. gcimpute can impute missing data with many different variable types, including continuous, binary, ordinal, count, and truncated values, by modeling data as samples from a Gaussian copula model. This semiparametric model learns the marginal distribution of each variable to
Yuxuan Zhao, Madeleine Udell
openaire   +4 more sources

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

CFMI: Flow Matching for Missing Data Imputation

CoRR
We introduce conditional flow matching for imputation (CFMI), a new general-purpose method to impute missing data. The method combines continuous normalising flows, flow-matching, and shared conditional modelling to deal with intractabilities of traditional multiple imputation.
Simkus, Vaidotas, Gutmann, Michael U.; id_orcid 0000-0002-5329-9910   +1 more
openaire   +3 more sources

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

Advanced Engineering Materials, EarlyView.
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, Sanxchep Sharma, Veit Königer, Vincent Nebel, Jonas Oehm, Christian Weisenberger, Laura Bies, Volker Knoblauch   +7 more
wiley   +1 more source