Results 201 to 210 of about 8,368,743 (296)

Natural Language Processing (NLP)- and Machine Learning (ML)-Enabled Operating Room Optimization: A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Systematic Review Anchored in Project Planning Theory. [PDF]

Cureus
Chamarthi B, Polu OR, Anumula SK, Ushmani A, Kasralikar P, Aleem Syed A.   +5 more
europepmc   +1 more source

Polyphenol‐Inspired Materials for Agricultural Applications

Advanced Materials, EarlyView.
This review outlines the use of polyphenol‐inspired materials for sustainable agriculture, highlighting their molecular design, interfacial assembly, structure–property relationships, and prospects toward precision agriculture, climate resilience, ecosystem protection, and circular bioeconomy strategies.
Haofu Liu, Omid Mazaheri, Zhixing Lin, Tianzheng Wang, Jingqu Chen, Yuang Gu, Xia Liang, Deli Chen, Frank Caruso   +8 more
wiley   +1 more source

Review of Inorganic Separator Engineering for Next‐Generation Lithium–Sulfur Batteries: Compromise or Cornerstone?

Advanced Materials, EarlyView.
Inorganic compound‐modified separators transform lithium–sulfur batteries from passive polysulfide confinement to active reaction‐pathway regulation. A Practical Relevance Index (PRI)‐guided framework bridges interfacial chemistry of inorganic separators with practical constraints, establishing unified design principles for scalable, high‐energy ...
Yuting Qin, Tianyi Wang, Xingyu Wang, Kaifu Xu, Yuzhou Wang, Chengyin Wang, Bing Sun, Guoxiu Wang   +7 more
wiley   +1 more source

Maximizing the performance of badminton athletes through core strength training: Unlocking their full potential using machine learning (ML) modeling. [PDF]

Heliyon
Ma S, Geok Soh K, Binti Japar S, Xu S, Zhicheng G.   +4 more
europepmc   +1 more source

Leveraging Data‐Driven and Fundamental Insights for Electrolyte Innovation in Lithium Metal Batteries

Advanced Materials, EarlyView.
Using 640 curated electrolyte formulations, we apply data‐driven analysis to reveal how molecular features govern coulombic efficiency (CE) in lithium metal batteries. Fluorine content correlates positively with CE, while oxygen, carbon, and higher boiling points correlate negatively.
Minh Van Duong, Mitchell Kaiser, Xia Cao, Trung Thien Nguyen, Au Nguyen, Phung My Loan Le, Jun Liu   +6 more
wiley   +1 more source

Position: topological deep learning is the new frontier for relational learning

Topological deep learning (TDL) is a rapidly evolving field that uses topological features to understand and design deep learning models. This paper posits that TDL is the new frontier for relational learning.
Nasrin, F, Ramamurthy, KN, Curry, J, Liò, P, Maroulas, V, Gao, Y, Carlsson, G, Kwitt, R, Wang, Y, Zamzmi, G, Veličković, P, Wang, B, Papamarkou, T, Hajij, M, Schaub, MT, Wei, GW, Scardapane, S, Bronstein, M, Birdal, T, Rieck, B, Miolane, N, Di Lorenzo, P   +21 more
core  

Erratum: Editorial note to "Maximizing the performance of badminton athletes through core strength training: Unlocking their full potential using machine learning (ML) modeling" [Heliyon 10(15), August 2024, e35145]. [PDF]

Heliyon
Ma S.
europepmc   +1 more source

Artificial Intelligence Meets Micro/Nanorobotics

Advanced Materials, EarlyView.
Artificial intelligence is transforming micro‐ and nanorobots from externally controlled, task‐specific machines into adaptive, autonomous systems. Machine learning, multimodal perception, digital twins, AI‐guided materials and geometry design enhance propulsion, localization, decision‐making, whichaccelerates clinical and environmental applications ...
Fatma M. Yurtsever, Minitha Cherukutty Ramakrishnan, Ian Kuula Ross, Ivan Zelinka, Hamed Shahsavan, Michal Otyepka, Martin Pumera   +6 more
wiley   +1 more source

Gaussian Processes with Bayesian Inference of Covariate Couplings

Publisher Copyright: © 2025, Transactions on Machine Learning Research. All rights reserved.Gaussian processes are powerful probabilistic models that are often coupled with Automatic Relevance Determination (ard) capable of uncovering the importance of ...
Rosso, Mattia, Filippone, Maurizio, Ylä-Jääski, Juho, Heinonen, Markus, Shen, Zheyang   +4 more
core  

An overview of the use of cutting-edge artificial intelligence (AI) modeling to produce synthetic medical data (SMD) in decentralized clinical machine learning (ML) for ovarian cancer(OC) and ovarian lymphoma(OL). [PDF]

J Ultrasound
Donatello D.
europepmc   +1 more source