Results 81 to 90 of about 216,838 (308)

Cognitive Behavioral Therapy for Youth With Childhood‐Onset Lupus: A Randomized Clinical Trial

Arthritis Care &Research, EarlyView.
Objective Our objective was to determine the feasibility and acceptability of the Treatment and Education Approach for Childhood‐Onset Lupus (TEACH), a six‐session cognitive behavioral intervention addressing depressive, fatigue, and pain symptoms, delivered remotely to individual youth with lupus by a trained interventionist.
Natoshia R. Cunningham, Thea Senger‐Carpenter, Jocelyn Zuckerman, Michelle Adler, Mallet R. Reid, Ashley Danguecan, Luana Flores Pereira, Sarah I. Mossad, Samantha L. Ely, Khalid Abulaban, Elizabeth A. Kessler, Natalie Rosenwasser, Tamar B. Rubinstein, Ekemini A. Ogbu, Emily A. Smitherman, Alaina Miller, Taylor Abounader, Elizabeth Ross, Livie Timmerman, Dhriti Sharma, Jennifer N. Stinson, Stacy Allen, Kabita Nanda, Tala El Tal, Deborah M. Levy, Linda T. Hiraki, Hermine I. Brunner, Mathew Reeves, Steven J. Pierce, Andrea Knight   +29 more
wiley   +1 more source

Using Visible Spectral Information to Predict Long-Wave Infrared Spectral Emissivity: A Case Study over the Sokolov Area of the Czech Republic with an Airborne Hyperspectral Scanner Sensor

Remote Sensing, 2013
Remote-sensing platforms are often comprised of a cluster of different spectral range detectors or sensors to benefit from the spectral identification capabilities of each range. Missing data from these platforms, caused by problematic weather conditions,
Gila Notesco, Eyal Ben-Dor, Simon Adar, Yoel Shkolnisky   +3 more
doaj   +1 more source

Imputation of Missing Data in Waves 1 and 2 of SHARE [PDF]

The Survey of Health, Ageing and Retirement in Europe (SHARE), like all large household surveys, suffers from the problem of item non-response, and hence the need of imputation of missing values arises. In this paper I describe the imputation methodology
Dimitrios Christelis
core  

Mycophenolate Mofetil Treatment Reduces the Risk of Treatment Escalation Due to Vascular Complications in Limited Cutaneous Systemic Sclerosis: Emulation of a Target Trial From the Italian Rheumatology Society SPRING Registry

Arthritis Care &Research, EarlyView.
Objective Mycophenolate mofetil (MMF) use in limited cutaneous systemic sclerosis (lcSSc) is relatively uncommon because of the lower fibrotic burden and the predominance of vascular complications. In vitro observations and clinical data from transplanted patients suggest a protective effect of MMF on endothelial function.
Enrico De Lorenzis, Gerlando Natalello, Rossella De Angelis, Lucrezia Verardi, Dilia Giuggioli, Gianluigi Bajocchi, Lorenzo Dagna, Silvia Bellando‐Randone, Giovanni Zanframundo, Rosario Foti, Fabio Cacciapaglia, Giovanna Cuomo, Alarico Ariani, Edoardo Rosato, Gemma Lepri, Francesco Girelli, Valeria Riccieri, Elisabetta Zanatta, Ilaria Cavazzana, Francesca Ingegnoli, Maria De Santis, Giuseppe Murdaca, Giuseppina Abignano, Giorgio Pettiti, Alessandra Della Rossa, Maurizio Caminiti, Annamaria Iuliano, Giovanni Ciano, Lorenzo Beretta, Gianluca Bagnato, Ennio Lubrano, Maria Ilenia De Andres, Alessandro Giollo, Cosimo Bruni, Martina Orlandi, Marco Fornaro, Marta Saracco, Cecilia Agnes, Pier Giacomo Cerasuolo, Gabriella Alonzi, Edoardo Cipolletta, Federica Lumetti, Amelia Spinella, Luca Magnani, Corrado Campochiaro, Giacomo De Luca, Veronica Codullo, Elisa Visalli, Carlo Iandoli, Antonietta Gigante, Greta Pellegrino, Erika Pigatto, Maria‐Grazia Lazzaroni, Franco Franceschini, Elena Generali, Gianna Mennillo, Simone Barsotti, Giuseppa Pagano Mariano, Federica Furini, Licia Vultaggio, Simone Parisi, Clara Lisa Peroni, Gerolamo Bianchi, Enrico Fusaro, Gian Domenico Sebastiani, Marcello Govoni, Salvatore D'Angelo, Franco Cozzi, Fabrizio Conti, Serena Guiducci, Andrea Doria, Carlo Salvarani, Florenzo Iannone, Maria Antonietta D'Agostino, Clodoveo Ferri, Marco Matucci Cerinic, Silvia Laura Bosello, on behalf of the SPRING Italian Registry Collaborators   +77 more
wiley   +1 more source

Can k-NN imputation improve the performance of C4.5 with small software project data sets? A comparative evaluation

, 2008
Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can tolerate missing values, namely C4.5, to predict cost using six real world
Liu, J, Song, Q, Shepperd, MJ, Chen, X
core   +1 more source

Addressing Economic Insecurities Can Improve Patient‐Reported Outcomes in Lupus

Arthritis Care &Research, EarlyView.
Objective Economic insecurities, such as food, housing, transportation, and financial challenges, are modifiable risk factors and influence patient‐reported outcomes (PROs) in systemic lupus erythematosus (SLE). We examined the following: (1) associations between economic insecurities and PROs, and (2) the impact of screening and addressing economic ...
Jay Patel, Tripti Singh, Meredith Ingersoll, Shelby Gomez, Amanda Weber, Sarah E. Panzer, Sancia Ferguson, Christie M. Bartels, Shivani Garg   +8 more
wiley   +1 more source

Propensity score matching with missing covariates via iterated, sequential multiple imputation

, 2011
In many observational studies, analysts estimate causal effects using propensity score matching. Estimation of propensity scores is complicated when covariate values intended for collection are in fact missing. To handle the missing data, one approach is
Reiter, Jerome P., Mitra, Robin
core  

Use of a Molecular Signature Response Classifier to Inform Treatment Selection Improves Clinical Disease Activity Among Patients with Rheumatoid Arthritis Initiating a Biologic or Targeted Synthetic Disease‐Modifying Antirheumatic Drug

Arthritis Care &Research, EarlyView.
Objective We assessed the effectiveness of PrismRA to improve clinical outcomes among patients with rheumatoid arthritis (RA) initiating treatment with a biologic or targeted synthetic disease‐modifying antirheumatic drug (b/tsDMARD). Methods PrismRA incorporated 19 gene expression features and four clinical features to assess a patient's likelihood of
Fenglong Xie, Timothy Beukelman, Nicholas P. McCormick, Jeffrey R. Curtis   +3 more
wiley   +1 more source

In-Database Data Imputation [PDF]

Proceedings of the ACM on Management of Data
Missing data is a widespread problem in many domains, creating challenges in data analysis and decision making. Traditional techniques for dealing with missing data, such as excluding incomplete records or imputing simple estimates (e.g., mean), are computationally efficient but may introduce bias and disrupt variable relationships, leading to ...
Massimo Perini, Milos Nikolic 0001
openaire   +2 more sources

A new hybrid method for data analysis when a significant percentage of data is missing [PDF]

Journal of Hyperstructures
This article aims to compare the efficiency of different imputation methods with missing data. In this way we use mean, median, Expected-Maximization (EM), regression imputation(RI) and multiple imputations (MI) to replace missing data.In fact, we employ
Behrouz Fathi-Vajargah, Ahmad Nouraldin
doaj   +1 more source