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BERN2: an advanced neural biomedical named entity recognition and normalization toolopen access

Authors
Sung, MujeenJeong, MinbyulChoi, YonghwaKim, DonghyeonLee, JinhyukKang, Jaewoo
Issue Date
14-10월-2022
Publisher
OXFORD UNIV PRESS
Citation
BIOINFORMATICS, v.38, no.20, pp.4837 - 4839
Indexed
SCIE
SCOPUS
Journal Title
BIOINFORMATICS
Volume
38
Number
20
Start Page
4837
End Page
4839
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/146558
DOI
10.1093/bioinformatics/btac598
ISSN
1367-4803
Abstract
In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e.g. diseases and drugs) from the ever-growing biomedical literature. In this article, we present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by employing a multi-task NER model and neural network-based NEN models to achieve much faster and more accurate inference. We hope that our tool can help annotate large-scale biomedical texts for various tasks such as biomedical knowledge graph construction.
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