Results 111 to 120 of about 47,614 (155)

A joint span-entity prediction approach with generative and cross-lingual meta-learning for low-resource Japanese NER. [PDF]

Sci Rep
Shao X, Zhu D, Liu Q, Pan X.
europepmc   +1 more source

Improving few-shot named entity recognition for large language models using structured dynamic prompting with retrieval augmented generation. [PDF]

NPJ Artif Intell
Ge Y, Guo Y, Das S, Sarker A.
europepmc   +1 more source

Bangla-MedER: An annotated Bangla dataset for multi-type medical entity recognition from medical text. [PDF]

Data Brief
Sheikh R, Rafiq SA, Hasan MM, Ahmed S, Aurpa TT, Akter F.   +5 more
europepmc   +1 more source

ANCHOLIK-NER: A benchmark dataset for Bangla regional named entity recognition. [PDF]

PLoS One
Paul B, Preotee FF, Sarker S, Refat SR, Islam S, Muhammad T, Hoque MA, Manzoor S.   +7 more
europepmc   +1 more source

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A review of biomedical named entity recognition

Journal of Computational Methods in Sciences and Engineering, 2022
Biomedical research on brucellosis has been a hot topic of discussion around the world. In the face of the complex literature, how to obtain the relevant research knowledge of brucellosis by biomedical experts has been a problem that researchers in this field have been working on.
Lu Chang, Ruihuan Zhang, Jia Lv, Weiguang Zhou, Yunli Bai   +4 more
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Accurate Clinical and Biomedical Named Entity Recognition at Scale

Software Impacts, 2022
Veysel Kocaman
exaly   +2 more sources

A Genetic Approach for Biomedical Named Entity Recognition

2010 22nd IEEE International Conference on Tools with Artificial Intelligence, 2010
In this paper, we report a classifier ensemble technique using the search capability of genetic algorithm (GA) for Named Entity Recognition (NER) in biomedical domain. We use Maximum Entropy (ME) framework to build a number of classifiers depending upon the various representations of a set of features.
Asif Ekbal, Sriparna Saha 0001, Utpal Kumar Sikdar, Mohammed Hasanuzzaman   +3 more
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A Hybrid Approach for Biomedical Entity Name Recognition

2009 2nd International Conference on Biomedical Engineering and Informatics, 2009
Biomedical named entity recognition, an important step, makes preparation for extracting information from biomedical textual resources. This paper presents a hybrid approach to recognize biomedical entity, which includes POS (Part-of-Speech) tagging, rules-based and dictionary-based approach using biomedical ontology.
Lejun Gong, Yi Yuan, You-Bing Wei, Xiao Sun 0006   +3 more
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Efficient Methods for Biomedical Named Entity Recognition

2007 IEEE 7th International Symposium on BioInformatics and BioEngineering, 2007
In recent years, conditional random fields (CRFs) have shown good performance in named entity recognition tasks. However, a direct application of it to biomedical named entity recognition incurs a very high training cost. In this paper, we evaluate two alternatives to training a CRF with a traditional single-phase maximum likelihood training method ...
Shing-Kit Chan, Wai Lam
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Biomedical Named Entity Recognition with less Supervision

2015 International Conference on Healthcare Informatics, 2015
Annotating clinical notes manually is very labor-intensive and needs expertise in the area of annotation. Thus annotation is a highly expensive task not only in human resource but also in financial aspects. Moreover mistakes, missed tags, and inconsistency are the common problems with manual annotations. The purpose of this research is to reduce humans
Omid Ghiasvand, Rohit J. Kate
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