Results 61 to 70 of about 418,591 (309)

Exploring Machine Translation on the Web [PDF]

Tradumàtica tecnologies de la traducció, 2010
This article briefly explores machine translation on the web, its history and current research. It briefly examines as well four free on-line machine translation engines in terms of language combinations offered, text length accepted and document formats supported as well as the quality of their raw MT output.
openaire   +7 more sources

Surfaceome: a new era in the discovery of immune evasion mechanisms of circulating tumor cells

Molecular Oncology, EarlyView.
In the era of immunotherapies, many patients either do not respond or eventually develop resistance. We propose to pave the way for proteomic analysis of surface‐expressed proteins called surfaceome, of circulating tumor cells. This approach seeks to identify immune evasion mechanisms and discover potential therapeutic targets. Circulating tumor cells (
Doryan Masmoudi, Jérome Vialaret, Christophe Hirtz, Catherine Alix‐Panabières   +3 more
wiley   +1 more source

Comparing Formulaic Language in Human and Machine Translation: Insight from a Parliamentary Corpus [PDF]

arXiv, 2022
A recent study has shown that, compared to human translations, neural machine translations contain more strongly-associated formulaic sequences made of relatively high-frequency words, but far less strongly-associated formulaic sequences made of relatively rare words.
arxiv  

Cell‐free and extracellular vesicle microRNAs with clinical utility for solid tumors

Molecular Oncology, EarlyView.
Cell‐free microRNAs (cfmiRs) are small‐RNA circulating molecules detectable in almost all body biofluids. Innovative technologies have improved the application of cfmiRs to oncology, with a focus on clinical needs for different solid tumors, but with emphasis on diagnosis, prognosis, cancer recurrence, as well as treatment monitoring.
Yoshinori Hayashi, Janelle‐Cheri Millen, Romela Irene Ramos, Jennifer A. Linehan, Timothy G. Wilson, Dave S. B. Hoon, Matias A. Bustos   +6 more
wiley   +1 more source

NanoCMSer: a consensus molecular subtype stratification tool for fresh‐frozen and paraffin‐embedded colorectal cancer samples

Molecular Oncology, EarlyView.
Consensus molecular subtypes (CMS1‐4) have been identified to study colorectal cancer heterogeneity and serve as potential biomarkers. In this study, we developed and evaluated NanoCMSer, a NanoString‐based classifier using 55 genes, optimized for FF and FFPE to facilitate the clinical evaluation of CMS subtyping.
Arezo Torang, Simone van de Weerd, Veerle Lammers, Sander van Hooff, Inge van den Berg, Saskia van den Bergh, Miriam Koopman, Jan N. IJzermans, Jeanine M. L. Roodhart, Jan Koster, Jan Paul Medema   +10 more
wiley   +1 more source

INTEGRATING MACHINE TRANSLATION AND SPEECH SYNTHESIS COMPONENT FOR ENGLISH TO DRAVIDIAN LANGUAGE SPEECH TO SPEECH TRANSLATION SYSTEM [PDF]

Journal of Engineering Science and Technology, 2015
This paper provides an interface between the machine translation and speech synthesis system for converting English speech to Tamil text in English to Tamil speech to speech translation system.
J. SANGEETHA, S. JOTHILAKSHMI
doaj  

Applying Automated Machine Translation to Educational Video Courses [PDF]

arXiv, 2023
We studied the capability of automated machine translation in the online video education space by automatically translating Khan Academy videos with state-of-the-art translation models and applying text-to-speech synthesis and audio/video synchronization to build engaging videos in target languages.
arxiv  

Extending a model for ontology-based Arabic-English machine translation [PDF]

International Journal of Artificial Intelligence and Applications (IJAIA), Vol.10, No.1, January 2019, 2019
The acceleration in telecommunication needs leads to many groups of research, especially in communication facilitating and Machine Translation fields. While people contact with others having different languages and cultures, they need to have instant translations.
arxiv   +1 more source

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Molecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison L. Creason, Robert Krueger, Jeremy Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Xie Yubin, Artem Sokolov, Darren R. Tyson   +16 more
wiley   +1 more source

Testing Machine Translation via Referential Transparency [PDF]

arXiv, 2020
Machine translation software has seen rapid progress in recent years due to the advancement of deep neural networks. People routinely use machine translation software in their daily lives, such as ordering food in a foreign restaurant, receiving medical diagnosis and treatment from foreign doctors, and reading international political news online ...
arxiv