Results 31 to 40 of about 47,614 (155)
Biomedical Named Entity Recognition at Scale [PDF]
, 2021 Named entity recognition (NER) is a widely applicable natural language processing task and building block of question answering, topic modeling, information retrieval, etc. In the medical domain, NER plays a crucial role by extracting meaningful chunks from clinical notes and reports, which are then fed to downstream tasks like assertion status ...
Veysel Kocaman, David Talby
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Biomedical Named Entity Recognition Method Based on Word Meaning Enhancement [PDF]
Jisuanji gongcheng, 2023 Biomedical Named Entity Recognition(BioNER), as a core task of biomedical text mining, provides strong support for downstream tasks. There are more unregistered words in biomedical data than in the general domain.
Mengxuan CHEN, Yanping CHEN, Ying HU, Ruizhang HUANG, Yongbin QIN
doaj +1 more source
Reranking for biomedical named-entity recognition [PDF]
Proceedings of the Workshop on BioNLP 2007 Biological, Translational, and Clinical Language Processing - BioNLP '07, 2007 This paper investigates improvement of automatic biomedical named-entity recognition by applying a reranking method to the COLING 2004 JNLPBA shared task of bioentity recognition. Our system has a common reranking architecture that consists of a pipeline of two statistical classifiers which are based on log-linear models.
Kazuhiro Yoshida, Jun'ichi Tsujii
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Named Entity Recognition for Chinese biomedical patents [PDF]
Proceedings of the 28th International Conference on Computational Linguistics, 2020 There is a large body of work on Biomedical Entity Recognition (Bio-NER) for English but there have only been a few attempts addressing NER for Chinese biomedical texts. Because of the growing amount of Chinese biomedical discoveries being patented, and lack of NER models for patent data, we train and evaluate NER models for the analysis of Chinese ...
Hu, Y., Verberne, S.
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Large-scale application of named entity recognition to biomedicine and epidemiology.
PLOS Digital Health, 2022 BackgroundDespite significant advancements in biomedical named entity recognition methods, the clinical application of these systems continues to face many challenges: (1) most of the methods are trained on a limited set of clinical entities; (2) these ...
Shaina Raza +3 more
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Unsupervised biomedical named entity recognition: Experiments with clinical and biological texts [PDF]
Journal of Biomedical Informatics, 2013 Noémie Elhadad
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Biomedical Named Entity Recognition with Multilingual BERT [PDF]
Proceedings of The 5th Workshop on BioNLP Open Shared Tasks, 2019 We present the approach of the Turku NLP group to the PharmaCoNER task on Spanish biomedical named entity recognition. We apply a CRF-based baseline approach and multilingual BERT to the task, achieving an F-score of 88% on the development data and 87% on the test set with BERT.
Hakala Kai, Pyysalo Sampo
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Improving named entity recognition accuracy for gene and protein in biomedical text literature [PDF]
, 2014 The task of recognising biomedical named entities in natural language documents called biomedical Named Entity Recognition (NER) is the focus of many researchers due to complex nature of such texts. This complexity includes the issues of character-level,
Azmi Murad, Masrah Azrifah +2 more
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Named Entity Recognition and Relation Detection for Biomedical Information Extraction
Frontiers in Cell and Developmental Biology, 2020 The number of scientific publications in the literature is steadily growing, containing our knowledge in the biomedical, health, and clinical sciences.
Nadeesha Perera +4 more
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Services for annotation of biomedical text [PDF]
, 2008 Motivation: Text mining in the biomedical domain in recent years has focused on the development of tools for recognizing named entities and extracting relations.
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