Results 101 to 110 of about 3,269 (255)
Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Abstract RETRACTION: J. Li, C. Tang, X. Zhang, R. Xing, and Q. Guo, “Histone Lactylation‐Driven Upregulation of VRK1 Expression Promotes Stemness and Proliferation of Glioma Stem Cells,” Advanced Science 12, no. 44 (2025): e03897, https://doi.org/10.1002/advs.202503897.
wiley +1 more source
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer +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
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
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
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 +2 more
wiley +1 more source
Body Cosmos 2.0: embodied biofeedback interface for dancing. [PDF]
Lin RR, Ke KY, Zhang K.
europepmc +1 more source
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
Advances in Materials Science and Engineering
doaj +1 more source

