Results 161 to 170 of about 3,760 (232)

Generative tissue modeling for customized biomechanical analysis: a data-driven synthesis framework of simulation-ready 3D shapes. [PDF]

Front Bioeng Biotechnol
Ma J, Wang Z, Wu Z, Li J, Lv Z, Cui T, Zhou B, Chen Y, Huang Y, Tang J.   +9 more
europepmc   +1 more source

Short‐Term Hourly Weather Forecasting Using PredRNN With Image Preprocessing

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Global weather forecast models are vital tools with numerous applications, including public safety, agriculture, and transportation. Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown the potential to enhance weather forecasting accuracy and speed.
Hoang Tran, Hao Li, Vinh Ngoc Tran, Tam V. Nguyen, Manh‐Hung Le, Thanh Duc Dang, Hong Xuan Do, Hung T. Pham, Tan Bui‐Thanh, L. Ruby Leung   +9 more
wiley   +1 more source

Unsupervised cross domain adaptive anomaly detection network for Internet of Things traffic. [PDF]

PLoS One
Yuan T, Zhai D, Li A.
europepmc   +1 more source

Data‐Driven Emulation of Numerically Simulated Baltic Sea Surface Currents With a Deep Convolutional U‐Net: Explainability and Potential Forecast Skill

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Ocean models can represent surface circulation at kilometer scales, but their computational cost limits broad experimentation. We present DeepCUN, a deep convolutional encoder–decoder (U‐Net) that emulates daily mean Baltic Sea surface current components on a 1‐nautical‐mile grid.
Amirhossein Barzandeh, Christoph Manss, Frederic Stahl, Ilja Maljutenko, Sander Rikka, Urmas Raudsepp   +5 more
wiley   +1 more source

Autoencoder Denoising for Network-Based Spatial Transcriptomics Data with Applications for Cell Signaling Estimation. [PDF]

Complex Netw Appl
Javaid A, Frost HR.
europepmc   +1 more source

Attention and Geological Knowledge Guided Spectral‐Spatial Networks for Geochemical Anomalies Recognition

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Achieving both accuracy and interpretability in deep learning models for geochemical anomaly recognition constitutes a significant challenge. To overcome this challenge, this study developed a novel interpretable dual‐branch network combining a spectral attention bidirectional RNN (BiRNN) branch and a spatial attention CNN branch guided with ...
Yihui Xiong, Zhixiang Liang, Zhiyi Chen, Yao Fan, Renguang Zuo   +4 more
wiley   +1 more source

Ultrasound - based deep learning radiomics nomogram for noninvasive prediction of p53 mutation status in hepatocellular carcinoma: a variational autoencoder based development and validation study. [PDF]

Front Oncol
Chen S, Qin X, Dong S, Qiu J, Liu Y, Liu Y, Zhu L, Li F.   +7 more
europepmc   +1 more source

PETIMOT: a novel framework for inferring protein motions from sparse data using SE(3)‐equivariant graph neural networks

Acta Crystallographica Section D, Volume 82, Issue 8, Page 862-885, August 2026.
We present a new formulation for protein flexibility and learn protein motions from sparse experimental data.Proteins move and deform to ensure their biological functions. Despite significant progress in protein structure prediction, approximating conformational ensembles under physiological conditions remains a fundamental open problem.
Valentin Lombard, Julien Nguyen Van, Sergei Grudinin, Elodie Laine   +3 more
wiley   +1 more source

Geometry-aware graph attention networks to explain single-cell chromatin states and gene expression with SEAGALL. [PDF]

Genome Biol
Malagoli G, Hanel P, Danese A, Wolf G, Colomé-Tatché M.   +4 more
europepmc   +1 more source

Integrating Artificial Intelligence Into Drug Discovery From Medicinal Plants: Current Applications and Infrastructural Challenges

Chemical Biology &Drug Design, Volume 108, Issue 2, August 2026.
This review presents a systems‐oriented roadmap for integrating artificial intelligence into medicinal plant drug discovery to overcome persistent bottlenecks like extract complexity. It highlights that advancing toward reproducible therapeutics requires making phytochemical datasets AI‐ready via rigorous harmonization and phyto‐centric foundational ...
Amit Gangwal, Azim Ansari, Mohd Usman Mohd Siddique, Jyotiram Sawale, Suhas Padmane, Raju Wadekar   +5 more
wiley   +1 more source