Results 221 to 230 of about 203,239 (310)
This perspective proposes a cohesive machine learning strategy to decode microplastic aging. It advocates for Federated Learning to dismantle global data silos and introduces the TRACE framework (TRansport, Aging, Corona, Ecotoxicity). By integrating physics‐informed modeling with causal discovery, this approach bridges the laboratory‐field gap to ...
Yaping Lyu +6 more
wiley +1 more source
Age Prediction of Hematoma from Hyperspectral Images Using Convolutional Neural Networks. [PDF]
Keshavarz A +4 more
europepmc +1 more source
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu +5 more
wiley +1 more source
Blind Image Quality Assessment Using Convolutional Neural Networks. [PDF]
Frackiewicz M, Palus H, Trojanowski W.
europepmc +1 more source
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou +8 more
wiley +1 more source
Predictive modeling of gene expression and localization of DNA binding site using deep convolutional neural networks. [PDF]
Karshenas A, Röschinger T, Garcia HG.
europepmc +1 more source
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley +1 more source
Deep Convolutional Neural Networks for Autofocus Control on a <i>C. elegans</i> Tracking System. [PDF]
Escobar-Benavides S +3 more
europepmc +1 more source
STransformer is a unified deep learning framework designed to seamlessly accommodate a comprehensive landscape of spatial data. By simultaneously capturing short‐range cellular interactions and tissue‐wide semantic patterns, it extracts robust representations to accurately dissect complex tissue heterogeneity.
Xingyi Li +9 more
wiley +1 more source
Development and validation of a blinding eye disease screening system based on lightweight convolutional neural networks: A diagnostic accuracy study. [PDF]
Gong R, Zheng H, Lang Z, Xu B, Jia W.
europepmc +1 more source

