MIAAIM: Multi-omics image integration with dimensional reduction for tissue state mapping. [PDF]
Hess JM +18 more
europepmc +1 more source
Hard‐Magnetic Soft Millirobots in Underactuated Systems
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang +4 more
wiley +1 more source
Feature fusion and WOA-GWO optimization for Alzheimer's disease detection with sparse EEG channels. [PDF]
Wang R +5 more
europepmc +1 more source
3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu +5 more
wiley +1 more source
AI and Machine Learning for Proteomics-Driven Drug Discovery: Methods, Tools, and Best Practices. [PDF]
Basak S.
europepmc +1 more source
Machine Learning and Artificial Intelligence in Nutrition Research: Analytical Methods, Applications, and Key Considerations. [PDF]
Southey NL, Zhu R, Holscher HD.
europepmc +1 more source
Image feature embedding with a deep learning framework improves genome-wide association studies on dog endophenotypes. [PDF]
E GX, Wang GD.
europepmc +1 more source
An evolutionary weighted feature influence factor feature selection method for fault detection in the Tennessee Eastman complex chemical process. [PDF]
Li D, Xue Y, Fu J, Tan T, Yang Y, Nie J.
europepmc +1 more source
Supervised Nonlinear Dimensionality Reduction for Visualization and Classification [PDF]
When performing visualization and classification, people often confront the problem of dimensionality reduction. Isomap is one of the most promising nonlinear dimensionality reduction techniques. However, when Isomap is applied to real-world data, it shows some limitations, such as being sensitive to noise. In this paper, an improved version of Isomap,
Xin Geng 0001 +2 more
exaly +4 more sources
Nonlinear dimensionality reduction with relative distance comparison [PDF]
This paper proposes a new algorithm for nonlinear dimensionality reduction. Our basic idea is to explore and exploit the local geometry of the manifold with relative distance comparisons. All such comparisons derived from local neighborhoods are enumerated to constrain the manifold to be learned.
Feiping Nie +2 more
exaly +4 more sources

