Results 141 to 150 of about 1,379,006 (264)

Conduction Aphasia in a Case of Left Cortical Veins and Left Lateral Sinus Thrombosis Due to Multiple Risk Factors: A Case Report and Review of the Literature. [PDF]

Life (Basel)
Munteanu G, Jianu SN, Bertici R, Iacob N, Dan TF, Jianu DC.   +5 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Design and methodology of the AI-empowered Clinical Evidence for Integrated Chinese-Western Medicine (ACE-iMed) platform. [PDF]

Integr Med Res
Liu H, Xu K, Zhang J, Wu S, Qin Y, Ma Y, Yu X, Zhang H, Li H, Wu M, Wang Z, Luo X, Wang B, Yao Y, Feng Y, Sun L, Dong M, Hong Y, Liu J, Yang R, Hu Y, Lai H, Zhou Q, Li X, Ge L, Chen Y, Bian Z.   +26 more
europepmc   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

A roadmap for medical large language models: a review of foundations, applications, and challenges. [PDF]

Mil Med Res
Sha YY, Yu L, Lin ZH, Kaur A, Lou YY, Gornale SS, Zhang TY, Wong LS, Wang ZW, Yan Y, Zhang XB, Hong R, Li K, Im SK, de Carvalho P, Tan T, Li KF.   +16 more
europepmc   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

An empirical study of intermediate and advanced Chinese learners of Japanese language about reading strategies based on think-aloud protocols. [PDF]

Front Psychol
Sun Y, Zhang M, Tan S.
europepmc   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Beyond Search Engine Optimization: How Large Language Models Are Redefining Surgeon Visibility. [PDF]

Plast Reconstr Surg Glob Open
Sorenson TJ, Boyd CJ, Hemal K, Cohen O, Karp N, Choi M.   +5 more
europepmc   +1 more source

The PRIMA Thesaurus for Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa, Alexey Boubnov, Dario De Angelis, Catriona Eschke, Maximilian Kabbe, Felix Kraus, Mirco Panighel, Richard Thelen, Davide Valentinis   +8 more
wiley   +1 more source