Results 221 to 230 of about 318,466 (281)

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

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

Bayesian network imputation methods applied to multi-omics data identify putative causal relationships in a type 2 diabetes dataset containing incomplete data: An IMI DIRECT Study. [PDF]

PLoS Genet
Howey R, Adam J, Adamski J, Atabaki NN, Brunak S, Chmura PJ, De Masi F, Dermitzakis ET, Fernandez-Tajes JJ, Forgie IM, Franks PW, Giordano GN, Haid M, Hansen T, Hansen TH, Harms PP, Hattersley AT, Hong MG, Jacobsen UP, Jones AG, Koivula RW, Kokkola T, Mahajan A, Mari A, McCarthy MI, McDonald TJ, Musholt PB, Pavo I, Pearson ER, Pedersen O, Ruetten H, Rutters F, Schwenk JM, Sharma S, 't Hart LM, Vestergaard H, Walker M, IMI DIRECT Consortium, Viñuela A, Cordell HJ.   +39 more
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +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

omicsMIC: a comprehensive benchmarking platform for robust comparison of imputation methods in mass spectrometry-based omics data. [PDF]

NAR Genom Bioinform
Lin W, Ji J, Su KJ, Qiu C, Tian Q, Zhao LJ, Luo Z, Wu C, Shen H, Deng H.   +9 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

Comparison of the effects of imputation methods for missing data in predictive modelling of cohort study datasets. [PDF]

BMC Med Res Methodol
Li J, Guo S, Ma R, He J, Zhang X, Rui D, Ding Y, Li Y, Jian L, Cheng J, Guo H.   +10 more
europepmc   +1 more source

An Integrated and Robust Deep Learning Framework for Denoising and Analyzing Single‐Cell Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
Single‐cell Spatial Transcriptomics Analysis and Denoising Engine is introduced as a unified deep learning framework that jointly performs denoising, clustering, and gene prioritization in spatial transcriptomics. By integrating linear and nonlinear representations within a dual‐channel architecture, it improves robustness and accuracy, uncovers ...
Yaxuan Cui, Yang Cui, Ruheng Wang, Xin Zeng, Zheyong Zhu, Ding Yi, Ruihua Guo, Tetsuya Sakurai, Kenta Nakai, Xiucai Ye, Leyi Wei, Yong Chen   +11 more
wiley   +1 more source

The impact of different imputation methods on estimates and model performance: an example using a risk prediction model for premature mortality. [PDF]

Popul Health Metr
Hurst M, O'Neill M, Pagalan L, Diemert LM, Rosella LC.   +4 more
europepmc   +1 more source