Results 31 to 40 of about 202,004 (267)
Context-Aware Data Imputation: Application of Domain-Agnostic Deep Imputation Network
IEEE AccessData imputation (DI) is a crucial task to manage missing data across different domains, such as healthcare and finance. Traditional imputation methods often fail to account for contextual nuances within specific domains due to the heterogeneity of data ...
Mohammed Gh. Al Zamil +1 more
doaj +1 more source
Referral Patterns and Diagnostic Timeliness in Pediatric Cancer: A Hospital‐Based Study in Indonesia
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Timely diagnosis and treatment are critical for improving survival among children with cancer. In low‐ and middle‐income countries (LMICs), delays are common and may be influenced by fragmented referral pathways and diagnostic limitations.
Nur Melani Sari +5 more
wiley +1 more source
Соціологічні студіїMissing categorical data presents a persistent challenge to data quality in quantitative sociological research, where simpler approaches can lead to biased estimates and incorrect conclusions.
Yaroslav Kostenko, Andrii Gorbachyk
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Reuse of imputed data in microarray analysis increases imputation efficiency [PDF]
BMC Bioinformatics, 2004 Abstract Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set.
Ki-Yeol Kim, Byoung-Jin Kim, Gwan-Su Yi
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Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Chronic micro‐inflammation in patients with end‐stage renal disease (ESRD) is a significant driver of cardiovascular complications and diminished quality of life. While standard hemodialysis (SHD) effectively manages small‐molecule clearance, its ability to remove medium‐to‐large uremic toxins—the primary catalysts of systemic ...
Hongwei Zuo +5 more
wiley +1 more source
Column-wise Guided Data Imputation [PDF]
Procedia Computer Science, 2017 Abstract This paper investigates data imputation techniques for pre-processing of dataset with missing values. The current literature is mainly focused on the overall accuracy, evaluated estimating the missing values on the dataset at hand, however the predictions can be suboptimal when considering the model performance for each feature.
Alessio Petrozziello, Ivan Jordanov
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Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Peripheral lysosomes recruit PLEKHG3 to focal adhesions and restrain protrusion dynamics
FEBS Letters, EarlyView.Proximity‐dependent labeling at the LAMTOR complex revealed the Rho GEF PLEKHG3 as a lysosome‐proximal protein directing the study toward the influence of lysosome positioning on actin dynamics and cell motility. We show that PLEKHG3 colocalizes with lysosomes at focal adhesion sites and observe that forced peripheral dispersion of lysosomes hinders ...
Rainer Ettelt +8 more
wiley +1 more source
Multiple imputation: dealing with missing data [PDF]
Nephrology Dialysis Transplantation, 2013 In many fields, including the field of nephrology, missing data are unfortunately an unavoidable problem in clinical/epidemiological research. The most common methods for dealing with missing data are complete case analysis-excluding patients with missing data--mean substitution--replacing missing values of a variable with the average of known values ...
Goeij, M.C.M. de +5 more
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FEBS Letters, EarlyView.This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source