Results 91 to 100 of about 155,766 (268)

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

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Combining link and content-based information in a Bayesian inference model for entity search

, 2012
An architectural model of a Bayesian inference network to support entity search in semantic knowledge bases is presented. The model supports the explicit combination of primitive data type and object-level semantics under a single computational framework.
Koumenides, Christos, Salvadores, Manuel, Omitola, Temitope, Shadbolt, Nigel   +3 more
core  

The Trichinella Super‐Pangenome Reveals the Evolution of Encapsulation and Predicted Host–Parasite Protein Interactions

Advanced Science, EarlyView.
ABSTRACT The muscle capsule of Trichinella is a critical structure that impedes immune attacks and drug penetration, yet the molecular mechanisms underlying its formation remain poorly understood. Using a high‐quality super‐pangenome comprising 12 Trichinella species, we compared extensive genomic variations between encapsulating and non‐encapsulating ...
Qingbo Lv, Yi Liu, Ning Xu, Xiao Zhang, Yaming Yang, Chengyao Li, Hanhai Mao, Mingyuan Liu, Xiaolei Liu   +8 more
wiley   +1 more source

Structural learning of bayesian networks using statistical constraints [PDF]

, 2012
Bayesian Networks are probabilistic graphical models that encode in a compact manner the conditional probabilistic relations over a set of random variables.
Venco, Francesco
core  

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

Design of Single‐Atom Nanozymes for Precision Treatment of Erectile Dysfunction with Integrated Single‐Cell RNA Sequencing and Machine Learning

Advanced Science, EarlyView.
It is innovatively utilized single‐cell RNA sequencing to explore the underlying causes of diabetes mellitus‐induced erectile dysfunction, followed by machine learning‐driven design of a single‐atom nanozyme (Fe‐DMOF) for precision treatment of erectile dysfunction.
Xiang Zhou, Xi Zhang, Sihan Chen, Mengchi Yu, Yilan Hu, Chi Gan, Xianghu Meng, Long Li, Ninghong Song   +8 more
wiley   +1 more source

Statistical model comparison applied to common network motifs

, 2010
Background: Network motifs are small modules that show interesting functional and dynamic properties, and are believed to be the building blocks of complex cellular processes.
Domedel Puig, N., Wernisch, Lorenz, Núria Domedel-Puig, Lorenz Wernisch, Pournara, Iosifina, Iosifina Pournara   +5 more
core   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

Sensor Planning for Mobile Robot Localization

, 2001
We propose a new method of sensor planning for mobile robot localization using Bayesian network inference. Since we can model causal relations between situations of the robot's behavior and sensing events as nodes of a Bayesian network, we can use ...
Using Bayesian Network, Shigeyuki Sakane, Hongjun Zhou   +2 more
core