Results 41 to 50 of about 131,123 (260)

Comparative Evaluation of Hemodiafiltration, Hemoperfusion, and Standard Hemodialysis on Efficacy, Inflammatory Control, Dialysis Adequacy, and Safety in End‐Stage Renal Disease: A Prospective Observational Study

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, Weisi Dai, Jie Mao, Mei Ye, Xingshan Lu, Xiaocui Zhang   +5 more
wiley   +1 more source

Investigation of the Multiple Imputation Method in Different Missing Ratios and Sample Sizes

Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2019
In many studies, missing data are thereal trouble to researchers. Because the statistical methods are designed forcomplete data sets. Multiple imputation method is developed to solve themissing data problem.
Nesrin Alkan, B. Baris Alkan
doaj   +1 more source

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, İsmail Güderer, Yi Wang, Tayyaba Alvi, Prasoon Pandey, Handan Melike Dönertaş   +5 more
wiley   +1 more source

QUIP: Query-driven Missing Value Imputation

CoRR, 2022
Missing values widely exist in real-world data sets, and failure to clean the missing data may result in the poor quality of answers to queries. \yiming{Traditionally, missing value imputation has been studied as an offline process as part of preparing data for analysis.} This paper studies query-time missing value imputation and proposes QUIP, which ...
Yiming Lin 0002, Sharad Mehrotra
openaire   +2 more sources

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, Ana‐Maria Sandru, Georg Vucak, Sebastian Didusch, Biljana Riemelmoser, Karin Ehrenreiter, Markus Hartl, Lukas A. Huber, Manuela Baccarini   +8 more
wiley   +1 more source

Epigenetic heterogeneity and plasticity in therapy‐induced tumor states through single‐cell multi‐omics

Molecular Oncology, EarlyView.
Single‐cell multi‐omics reveals epigenetic heterogeneity across therapy‐adaptive tumor states, including quiescent/dormant, drug‐tolerant persister, and EMT‐like phenotypes. By linking regulatory features with state‐associated biomarkers, these approaches inform biomarker‐guided therapeutic strategies for evolving tumors.
Hee Jung Kim, Hwiyeong Lee, Jin Hong, Daechan Park   +3 more
wiley   +1 more source

DBSCANI: Noise-Resistant Method for Missing Value Imputation

Journal of Intelligent Systems, 2016
The quality of data is an important task in the data mining. The validity of mining algorithms is reduced if data is not of good quality. The quality of data can be assessed in terms of missing values (MV) as well as noise present in the data set ...
Purwar Archana, Singh Sandeep Kumar
doaj   +1 more source

Spatial and single‐nuclei transcriptomics reveals idiosyncratic and generic patterns in papillary and anaplastic thyroid cancers

Molecular Oncology, EarlyView.
Matched spatial transcriptomics and single‐nuclei RNA‐seq were generated for anaplastic and BRAFV600E papillary thyroid cancers revealing generic and tumor‐specific states occurring in cancer cells and in the tumor microenvironment. In this context, cancer dedifferentiation mirrored organoid maturation through ordered thyroid marker gain/loss ...
Adrien Tourneur, Joel Rodrigues Vitória, Manuel Saiselet, Ligia Craciun, Denis Larsimont, Anne Lefort, Frédérick Libert, Carine Maenhaut, Sabine Costagliola, Maxime Tarabichi, Mirian Romitti, Vincent Detours   +11 more
wiley   +1 more source

Missing values imputation using Fuzzy K-Top Matching Value

Journal of King Saud University: Computer and Information Sciences, 2023
Missing data occurs when variables or observations are missing. Researchers exclude or impute influenced variables and data. This study proposes Fuzzy K-Top Matching Value (FKTM) for missing value imputation.
Azza Ali, Mervat Abu-Elkheir, Ahmed Atwan, Mohammed Elmogy   +3 more
doaj   +1 more source

Imputing missing covariate values for the Cox model [PDF]

Statistics in Medicine, 2009
AbstractMultiple imputation is commonly used to impute missing data, and is typically more efficient than complete cases analysis in regression analysis when covariates have missing values. Imputation may be performed using a regression model for the incomplete covariates on other covariates and, importantly, on the outcome. With a survival outcome, it
White, Ian R, Royston, Patrick
openaire   +2 more sources