Results 171 to 180 of about 57,532 (265)

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
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

Correction: Mijović et al. Health in All Policies in Sectoral Legislation: A Content Analysis of Selected Laws in the Republic of Srpska. <i>Healthcare</i> 2026, <i>14</i>, 2139. [PDF]

Healthcare (Basel)
Mijović B, Joksimović B, Dubravac Tanasković M, Kulić J, Stojanović Z, Stojić N, Milošević L, Panin B, Ćurčić G, Prokić D, Malbasa JD, Duric P.   +11 more
europepmc   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Genomic Data Governance Challenges Between Research and Clinical Care: A Scoping Review. [PDF]

Health Expect
Kim A, Merner B, Taylor M, Luo Y, Cannizzo F, Petersen A, Gaff C, Newson AJ, Marchant K, Keogh L.   +9 more
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Election Defined. [PDF]

Oxf J Leg Stud
Frey M.
europepmc   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

SMART CONTRACT IN CONTRACT LAW

Journal of Foreign Legislation and Comparative Law, 2019
openaire   +1 more source

Has the new Scottish GP contract improved GPs' working lives in deprived areas? A secondary analysis of two cross-sectional national surveys of GPs' views in 2018 and 2023. [PDF]

BJGP Open
Ng L, Lunan CJ, Mercer SW.
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source