Opportunities and Challenges in Using National EHR Networks for AI in Learning Health Systems. [PDF]
Kukhareva PV +3 more
europepmc +1 more source
Distributions of intrinsic stacking fault energies (ISFE) among different slip planes in the face‐centered cubic Co2Ni2Ru alloy, predicted by three foundation potentials (DPA, Orb, and SevenNet) and density functional theory (DFT) calculations. This study evaluates the efficacy of three foundation potentials (FPs)—SevenNet, DPA, and Orb—in predicting ...
Subah Mubassira +8 more
wiley +1 more source
Prevalence and Risk Factors of Work-Related Musculoskeletal Disorders Among Dockworkers: The Role of Psychosocial Stress and Physical Demands in an Iranian Port. [PDF]
Tajvar A, Mohseni S, Kazempour M.
europepmc +1 more source
AI Powered Biobanks From Static Archives to Dynamic Discovery Engines
Large language models (LLMs) provide a potential framework for transforming biobanks from static data repositories into intelligent discovery engines. By enabling unified representation and analysis of multimodal biomedical data, LLM‐based systems facilitate dynamic risk prediction, biomarker identification, and mechanistic interpretation, thereby ...
Wenzhen Yin +5 more
wiley +1 more source
This article implements a unified human digital twin framework that integrates cutting edge actuation, sensing, simulation, and bidirectional feedback capability. The approach includes integrating multimodal sensing, AI, and biomechanical simulation into one compact system.
Tajbeed Ahmed Chowdhury +4 more
wiley +1 more source
Optimizing multi-level shuttle-based puzzle storage systems with horizontal and vertical dynamics using integer programming and ALNS-IP. [PDF]
Al Jneid R, Yiğit V, Keskin ME.
europepmc +1 more source
Holographic Mapping of Orbital Angular Momentum using a Terahertz Diffractive Optical Neural Network
A compact six‐layer diffractive optical neural network enables direct recognition and spatial mapping of terahertz (THz) orbital angular momentum (OAM) beams. Fabricated by 3D printing, the system distinguishes nine OAM modes and their superpositions with high fidelity, good efficiency, and low crosstalk, offering a scalable solution for THz ...
Wei Jia +3 more
wiley +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong +5 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source

