Results 251 to 260 of about 4,220,052 (297)
A diachronic study determining syntactic and semantic features of Urdu-English neural machine translation. [PDF]
Shah TZ, Imran M, Ismail SM.
europepmc +1 more source
Analysis of Chinese Machine Translation Training Based on Deep Learning Technology.
Sun Y.
europepmc +1 more source
Retrospective Review on Reticular Materials: Facts and Figures Over the Last 30 Years
To shape the future course of research in reticular materials, this work reflects on the progress over the past 30 years, complemented by input from the community of 228 active researchers through a global, crowdsourced survey: ranging from demographics, how it works, publish and interact, to highlights on both academic and industrial milestones, as ...
Aamod V. Desai+8 more
wiley +1 more source
English-Chinese Machine Translation Based on Transfer Learning and Chinese-English Corpus.
Xu B.
europepmc +1 more source
This review explores how in situ and operando spectroscopic techniques reveal the real‐time behavior of reticular materials, including MOFs and COFs. These methods track material formation and functionalization, structural changes, defect formation, dynamic responses to external triggers, and catalytic processes.
Bettina Baumgartner+4 more
wiley +1 more source
Neural machine translation of clinical text: an empirical investigation into multilingual pre-trained language models and transfer-learning. [PDF]
Han L+5 more
europepmc +1 more source
This article summarizes significant technological advancements in materials, photonic devices, and bio‐interfaced systems, which demonstrate successful applications for impacting human healthcare via improved therapies, advanced diagnostics, and on‐skin health monitoring.
Seunghyeb Ban+5 more
wiley +1 more source
This review explores the integration of responsive materials and soft robotic actuators with implantable electronics to address key challenges in bioelectronic medicine. By enabling shape actuation, these technologies improve deployment, adaptability, and accuracy in minimally invasive procedures.
Chaoqun Dong, George G. Malliaras
wiley +1 more source
Machine‐Learning‐Aided Advanced Electrochemical Biosensors
Electrochemical biosensors are highly sensitive, portable, and versatile. Advanced nanomaterials enhance their performance, while machine learning (ML) improves data analysis, minimizes interference, and optimizes sensor design. Despite progress in both fields, their combined potential in diagnostics remains underexplored.
Andrei Bocan+9 more
wiley +1 more source