Results 51 to 60 of about 65,893 (254)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Multivariate Perturbed Hyperbolic Tangent-Activated Singular Integral Approximation

Mathematics
Here we study the quantitative multivariate approximation of perturbed hyperbolic tangent-activated singular integral operators to the unit operator. The engaged neural network activation function is both parametrized and deformed, and the related kernel
George A. Anastassiou
doaj   +1 more source

Understanding Fabrication Variability in Core‐Shell Soft Biomaterials Using Stochastic Artificial Intelligence

Advanced Science, EarlyView.
Fabrication‐induced variability remains a fundamental limitation in the scalable design of soft biomaterials. In this work, a stochastic machine learning approach based on Gaussian processes modeling is employed to establish quantitative links between biofabrication parameters, material properties, and their intrinsic variability.
Maria Alexaki, Lília M. S. Dias, Raquel C. Gonçalves, Dinis O. Abranches, Albano N. Carneiro Neto, Rute A. S. Ferreira, Paulo S. B. André, João F. Mano, Mariana B. Oliveira   +8 more
wiley   +1 more source

Multiple-Composite Quantitative Approximation by Multivariate Kantorovich–Choquet Neural Networks

Mathematics
In this work we study the univariate and multivariate quantitative approximation by multi-composite Kantorovich–Choquet-type quasi-interpolation neural network operators with respect to the supremum norm.
George A. Anastassiou
doaj   +1 more source

NIR‐II Imaging‐Guided Photothermal Activation of a TRPV4‐Targeted Nanoplatform Delivering Cycloastragenol to Promote Microglia Reprogramming and α‐Synuclein Clearance in Parkinson's Disease

Advanced Science, EarlyView.
ABSTRACT Current therapies for Parkinson's disease (PD) fail to concurrently address α‐synuclein (α‐syn) aggregation and microglia‐mediated neuroinflammation. Herein, we engineer a near‐infrared‐II (NIR‐II) phototheranostic nanoplatform, CAG/FD1080@MM‐aTRPV4, for synergistic regulation of microglial function and real‐time monitoring of PD pathology. We
Hsuan Lo, Linjuan Feng, Shiying Li, Lik Hang Hugo Tse, Xuehan Wang, Xingyang Zhao, Shaoheng Ma, Xin Li, Yanjuan Gu, Wing‐Tak Wong   +9 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

From Materials to Systems: Challenges and Solutions for Fast‐Charge/Discharge Na‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review systematically analyzes the key characteristics limiting the fast‐charge/discharge capability of Na‐ion batteries (SIBs) from a multi‐scale perspective encompassing electrode materials, the electrode‐electrolyte interface, and the system. Furthermore, it presents practical solution strategies for the fundamental issues arising at each scale,
Bonyoung Ku, Sangbin Park, Sunha Hwang, Sunghyun Lim, Won‐Sub Yoon, Jongsoon Kim   +5 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Feature embedded attention based hybrid approach for athletic injury risk prediction

Alexandria Engineering Journal
With the advancement of artificial intelligence driven athletes monitoring techniques, the sports analytics ecosystem gains multimodal observations for analyzing injury paradigm, providing abundant data sources for reliable athletes injury prediction ...
Mengqi Hu, Zhiqiang Song, Xiaoling Feng
doaj   +1 more source

Multivariate Jackson-type inequality for a new type neural network approximation

Applied Mathematical Modelling, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lin, Shaobo, Rong, Yuanhua, Xu, Zongben
openaire   +1 more source