Results 71 to 80 of about 179,516 (314)
Five‐Year Disease Progression in Synuclein Seeding Positive Sporadic Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To provide a comprehensive description of disease progression in synuclein seeding assay (SAA) positive sporadic Parkinson Disease participants, using Neuronal Synuclein Disease integrated biological and functional impairment staging framework.
Paulina Gonzalez‐Latapi +19 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective In multiple sclerosis, the optimal time for deploying a therapeutic intervention is before the central nervous system is damaged; given the success of trials treating the earliest stage of MS, the radiologically isolated syndrome, developing primary prevention strategies is an important next challenge.
Amy W. Laitinen +7 more
wiley +1 more source
Nonparametric Mass Imputation for Data Integration
Journal of Survey Statistics and Methodology, 2020 Abstract Data integration combining a probability sample with another nonprobability sample is an emerging area of research in survey sampling. We consider the case when the study variable of interest is measured only in the nonprobability sample, but comparable auxiliary information is available for both data sources.
Sixia, Chen, Shu, Yang, Jae Kwang, Kim
openaire +3 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Onasemnogene abeparvovec (OA) is an AAV9‐based gene therapy for spinal muscular atrophy type I (SMA I). Real‐world outcomes show increased response variability compared to clinical trials, and follow‐up data beyond 12–18 months are limited.
Marika Pane +43 more
wiley +1 more source
Evaluating Performance of Missing Data Imputation Methods in IRT Analyses
International Journal of Assessment Tools in Education, 2018 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
Financial Distress and Its Determinants in Rheumatoid Arthritis
Arthritis Care &Research, EarlyView.Objective To quantify the degree of financial distress and identify its determinants in adults with rheumatoid arthritis (RA) given the frequent prolonged use of expensive disease‐modifying therapies. Methods We identified adults enrolled in the FORWARD databank with either RA or noninflammatory musculoskeletal disease (NIMSKD) completing the ...
Amber Brown Keebler +5 more
wiley +1 more source
A Comparative Study on Missing Value Imputation Techniques in Machine Learning [PDF]
SHS Web of ConferencesHandling missing values is a crucial step in data preprocessing, as incomplete data can significantly impact model performance and overall data integrity.
Meng Haoyu
doaj +1 more source
Best Practices for Addressing Missing Data through Multiple Imputation
, 2021 Adrienne D. Woods +18 more
openalex +1 more source
Arthritis Care &Research, EarlyView.Objective We aimed to test the efficacy of personalized treatment of older veterans with chronic low back pain (CLBP) delivered by Aging Back Clinics (ABCs) as compared with usual care (UC). Methods Two hundred ninety‐nine veterans aged 65 to 89 with CLBP from three Veterans Affairs (VA) medical centers underwent baseline testing, randomization to ABC ...
Debra K. Weiner +9 more
wiley +1 more source
An Imputation Method for Missing Data Based on an Extreme Learning Machine Auto-Encoder
IEEE Access, 2018 This paper proposes an imputation method for missing data based on an extreme learning machine auto-encoder (ELM-AE). The imputation chooses a set of plausible values determined by ELM-AE and then substitutes the average of these plausible values for the
Cheng-Bo Lu, Ying Mei
doaj +1 more source