Results 141 to 150 of about 159,661 (256)

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

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +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

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 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

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

Advanced Intelligent Discovery, EarlyView.
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong, Lejia Wang, Tianqing Zhu, Keith Butler, Sichao Li   +4 more
wiley   +1 more source

Age-specific breast cancer incidence by subtype, TNM stage and screening status in Sweden 2008-2019 estimated with multiple imputation. [PDF]

Int J Cancer
Gkekos L, Gunnarsdóttir KÁ, Humphreys K, Fredriksson I, Johansson ALV.   +4 more
europepmc   +1 more source

Collaborative Visual Localization for Modular Self‐Reconfigurable Robots

Advanced Intelligent Systems, EarlyView.
Relative localization in modular self‐reconfigurable robots is challenged by hardware limitations, constrained fields of view, and sensor faults. This paper, based on the SnailBot platform, presents a vision‐based collaborative localization method that combines ArUco markers with learning‐based algorithms to enable robust pose estimation from ...
Guanqi Liang, Rong Ou, Peiqi Wang, Xianghong Wang, Tin Lun Lam   +4 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

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source