Results 161 to 170 of about 290,361 (291)

Improving Genotype Imputation in High-Dimensional Pharmacogenomics Using Multiple Imputation: Evaluation with Machine Learning Approaches. [PDF]

Clin Pharmacol Ther
Asiimwe IG, You T, Carr DF, Pirmohamed M, Davies G, Jorgensen AL, UNITE4TB Consortium.   +6 more
europepmc   +1 more source

Advancing European Plant Variety Registration: Data‐Driven Insights and Stakeholder Perspectives

Agribusiness, EarlyView.
ABSTRACT Efficient plant variety registration is crucial for fostering innovation in the European Union, yet the current regulatory framework is complex and faces calls for reform. This study provides data‐driven evidence to inform the ongoing legislative debate by employing a mixed‐methods approach.
Sergio Urioste Daza, Ibtissem Taghouti, José María Gil Roig   +2 more
wiley   +1 more source

High-dimensional multiple imputation for partially observed confounders including natural language processing-derived auxiliary covariates. [PDF]

Am J Epidemiol
Weberpals J, Shaw PA, Lin KJ, Wyss R, Plasek JM, Zhou L, Ngan K, DeRamus T, Raman SR, Hammill BG, Lee H, Toh S, Connolly JG, Dandreo KJ, Tian F, Liu W, Li J, Hernández-Muñoz JJ, Schneeweiss S, Desai RJ.   +19 more
europepmc   +1 more source

Multifactor Risk Stratification for Post‐Transplant Alcohol Relapse Using Abstinence, Psychosocial, and Socioeconomic Factors

Annals of Gastroenterological Surgery, EarlyView.
Alcohol relapse after liver transplantation is difficult to predict using abstinence duration alone. We developed a multifactor model integrating abstinence duration, psychosocial risk (SIPAT), and socioeconomic context (AUC 0.70). This approach may support individualized risk assessment and tailored follow‐up intensity; external validation is needed ...
Ayato Obana, Garren Montgomery, Miho Akabane, Matthew Hamilton, Navdeep Singh, Musab Alebrahim, Austin Schenk, Sylvester Black, Kenneth Washburn, Khalid Mumtaz   +9 more
wiley   +1 more source

Multiple imputation of multilevel data with single-level models: A fully conditional specification approach using adjusted group means. [PDF]

Behav Res Methods
Grund S, Lüdtke O, Robitzsch A.
europepmc   +1 more source

Reaction kinetics model in liquid and solid phases and its parameterization for room temperature sodium–sulfur battery

AIChE Journal, EarlyView.
Abstract A multipore, multiphase, continuum model is assembled for the first time for room temperature sodium–sulfur (RT Na–S) batteries, with Na+ ion transport and redox reactions in the liquid electrolyte phase and semisolid phase of precipitates softened by the electrolyte solvent, as guided by molecular dynamics simulations in this study ...
Hakeem A. Adeoye, Allan Foster, John F. Watts, Constantina Lekakou   +3 more
wiley   +1 more source

A Bayesian Two-Step Multiple Imputation Approach Based on Mixed Models for Missing EMA Data. [PDF]

Stat Med
Wei Y, Siddique J, Spring B, Hedeker D.
europepmc   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Multiple Imputation of Missing Covariates When Using the Fine-Gray Model. [PDF]

Stat Med
Bonneville EF, Beyersmann J, Keogh RH, Bartlett JW, Morris TP, Polverelli N, de Wreede LC, Putter H.   +7 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source