Results 51 to 60 of about 2,584,993 (291)

Neural Named Entity Recognition for Kazakh

, 2023
We present several neural networks to address the task of named entity recognition for morphologically complex languages (MCL). Kazakh is a morphologically complex language in which each root/stem can produce hundreds or thousands of variant word forms.
Gulmira Tolegen, Alymzhan Toleu, Orken Mamyrbayev, Rustam Mussabayev   +3 more
openaire   +4 more sources

Named Entity Recognition as Dependency Parsing [PDF]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020
Accepted by ACL ...
Juntao Yu, Bernd Bohnet, Massimo Poesio
openaire   +2 more sources

Oncogenic DMTF1β promotes cancer cell motility by regulating autophagy through ULK1 stabilization

Molecular Oncology, EarlyView.
In the current study, we demonstrate that the oncogene DMTF1β regulates ULK1 stability by reducing its proteasomal degradation in cancer cells. This stabilization enables ULK1 to induce autophagy, which in turn facilitates cancer cell migration. Consequently, reduced DMTF1β levels lead to decreased autophagy and impaired cancer cell migration.
Jun Xu, Nicolas J. Niklaus, Anna M. Schläfli, Igor Tokarchuk, Magali Humbert, Federico La Manna, Bich Vu, David Maul, Ramin Radpour, Marianna Kruithof‐de Julio, Inti Zlobec, Jörn Dengjel, Bruce E. Torbett, Mario P. Tschan   +13 more
wiley   +1 more source

HMM based Korean Named Entity Recognition [PDF]

Journal of Systemics, Cybernetics and Informatics, 2003
In this paper, we present a named entity recognition model for Korean Language. Named entity recognition is an essential and important process of Question Answering and Information Extraction system.
Yi-Gyu Hwang, Eui-Sok Chung, Soo-jong Lim   +2 more
doaj  

Automatic Construction of Chinese Nested Named Entity Recognition Corpus Based on Wikipedia [PDF]

Jisuanji gongcheng, 2018
Traditional supervised learning method needs to label the corpus in a certain scale,which limits its domain adaptability.Therefore,a method of automatically constructing a Chinese nested named entity recognition corpus from Chinese Wikipedia entries is ...
LI Yanqun,HE Yunqi,QIAN Longhua,ZHOU Guodong
doaj   +1 more source

Deep learning for named entity recognition in Turkish radiology reports. [PDF]

Diagn Interv Radiol
PURPOSE: The primary objective of this research is to enhance the accuracy and efficiency of information extraction from radiology reports. In addressing this objective, the study aims to develop and evaluate a deep learning framework for named entity ...
Abdullahi AA, Ganiz MC, Koç U, Gökhan MB, Aydın C, Özdemir AB.   +5 more
europepmc   +2 more sources

A named entity recognition dataset for Turkish

2016 24th Signal Processing and Communication Application Conference (SIU), 2016
Named entity recognition is one of the important topics in the research area of natural language processing. Named entity recognition studies conducted on Turkish texts are quite limited, compared to the studies on other languages. Besides, the lack of common data sets makes the comparison of different approaches harder.
Dilek Küçük, Dogan Küçük, Nursal Arici   +2 more
openaire   +4 more sources

Cancer‐associated mutations in endometriosis reframe a benign disease through molecular oncology

Molecular Oncology, EarlyView.
This review aims to comprehensively analyse cancer‐associated somatic mutations (CAMs) present in endometriotic lesions, emphasizing their biological roles, spatial distribution and implications for translational applications in medicine. By contextualizing a benign state within a genomic framework, this analysis seeks to establish its value as a ...
Clarissa Mujacic, Maria Concetta Vitale, Rita Siino, Emilia Di Giovanni, Carla Ferrante Bannera, Enrico Di Marco, Andrea Gottardo, Tancredi Didier Bazan Russo, Nadia Barraco, Alessandro Perez, Valerio Gristina, Antonio Galvano, Giuseppe Badalamenti, Antonio Russo, Viviana Bazan, Lorena Incorvaia   +15 more
wiley   +1 more source

A Named Entity Recognition System for Dutch [PDF]

, 2002
We describe a Named Entity Recognition system for Dutch that combines gazetteers, hand-crafted rules, and machine learning on the basis of seed material. We used gazetteers and a corpus to construct training material for Ripper, a rule learner. Instead of using Ripper to train a complete system, we used many different runs of Ripper in order to derive ...
De Meulder, Fien, Daelemans, Walter, Hoste, Veronique   +2 more
openaire   +5 more sources

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source