Results 101 to 110 of about 491,933 (328)

Semantic Neural Machine Translation Using AMR

open access: yesTransactions of the Association for Computational Linguistics, 2019
It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many sentences correspond to one meaning) of machine translation models.
Song, Linfeng   +4 more
doaj   +1 more source

Residual Information Flow for Neural Machine Translation

open access: yesIEEE Access, 2022
Automatic machine translation plays an important role in reducing language barriers between people speaking different languages. Deep neural networks (DNN) have attained major success in diverse research fields such as computer vision, information ...
Shereen A. Mohamed   +2 more
doaj   +1 more source

Single‐cell insights into the role of T cells in B‐cell malignancies

open access: yesFEBS Letters, EarlyView.
Single‐cell technologies have transformed our understanding of T cell–tumor cell interactions in B‐cell malignancies, revealing new T‐cell subsets, functional states, and immune evasion mechanisms. This Review synthesizes these findings, highlighting the roles of T cells in pathogenesis, progression, and therapy response, and underscoring their ...
Laura Llaó‐Cid
wiley   +1 more source

Supervised Attentions for Neural Machine Translation

open access: yes, 2016
In this paper, we improve the attention or alignment accuracy of neural machine translation by utilizing the alignments of training sentence pairs. We simply compute the distance between the machine attentions and the "true" alignments, and minimize this
Ittycheriah, Abe   +2 more
core   +1 more source

Unlocking the potential of tumor‐derived DNA in urine for cancer detection: methodological challenges and opportunities

open access: yesMolecular Oncology, EarlyView.
Urine is a rich source of biomarkers for cancer detection. Tumor‐derived material is released into the bloodstream and transported to the urine. Urine can easily be collected from individuals, allowing non‐invasive cancer detection. This review discusses the rationale behind urine‐based cancer detection and its potential for cancer diagnostics ...
Birgit M. M. Wever   +1 more
wiley   +1 more source

Targeting the AKT/mTOR pathway attenuates the metastatic potential of colorectal carcinoma circulating tumor cells in a murine xenotransplantation model

open access: yesMolecular Oncology, EarlyView.
Dual targeting of AKT and mTOR using MK2206 and RAD001 reduces tumor burden in an intracardiac colon cancer circulating tumor cell xenotransplantation model. Analysis of AKT isoform‐specific knockdowns in CTC‐MCC‐41 reveals differentially regulated proteins and phospho‐proteins by liquid chromatography coupled mass spectrometry. Circulating tumor cells
Daniel J. Smit   +19 more
wiley   +1 more source

Context Gates for Neural Machine Translation [PDF]

open access: yesTransactions of the Association for Computational Linguistics, 2017
In neural machine translation (NMT), generation of a target word depends on both source and target contexts. We find that source contexts have a direct impact on the adequacy of a translation while target contexts affect the fluency. Intuitively, generation of a content word should rely more on the source context and generation of a functional word ...
Zhengdong Lu   +4 more
openaire   +4 more sources

Ubiquitination of transcription factors in cancer: unveiling therapeutic potential

open access: yesMolecular Oncology, EarlyView.
In cancer, dysregulated ubiquitination of transcription factors contributes to the uncontrolled growth and survival characteristics of tumors. Tumor suppressors are degraded by aberrant ubiquitination, or oncogenic transcription factors gain stability through ubiquitination, thereby promoting tumorigenesis.
Dongha Kim, Hye Jin Nam, Sung Hee Baek
wiley   +1 more source

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

open access: yesMolecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima   +6 more
wiley   +1 more source

The neural machine translation of dislocations

open access: yesProceedings of International Conference of Experimental Linguistics, 2022
This paper investigates neural machine translation (NMT) outputs for dislocated constructions from French into English. Dislocations are often considered to be “substandard in formal registers” (Lambrecht 1994: 12). In French, multiple copies of the subject are licit in spoken data, whereas translations into English preclude them (De Cat 2007).
Namdarzadeh, Behnoosh, Ballier, Nicolas
openaire   +2 more sources

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