Results 211 to 220 of about 177,188 (278)

Automatic generation and transfer of Yongju opera language using AIGC technology and style mapping. [PDF]

Sci Rep
Meng X, Hu P, Li Z.
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Steady-state EEG captures how elementary classroom instruction drives plasticity for novel visual words. [PDF]

NPJ Sci Learn
Wang F, Toomarian EY, Gosavi RS, Kaneshiro B, Norcia AM, McCandliss BD.   +5 more
europepmc   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

PhyloFusion-Fast and Easy Fusion of Rooted Phylogenetic Trees into Rooted Phylogenetic Networks. [PDF]

Syst Biol
Zhang L, Cetinkaya B, Huson DH.
europepmc   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Performance analysis of concatenated Reed-Solomon and next generation polar codes for 6G communication systems. [PDF]

Sci Rep
Wondimu E, Annamalai P, Gared F.
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Performance evaluation of the ACTIVE 7 MAX benchtop preclinical PET scanner in accordance with the NEMA NU 4-2008 standard. [PDF]

EJNMMI Phys
Wang H, Wang K, Yuan Z, Li C, Liao R, Hou Y, Hua J, Tang Y, Ruan Q, Han D, Jiang J.   +10 more
europepmc   +1 more source