BioBERT: a pre-trained biomedical language representation model for biomedical text mining
Abstract Motivation Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep lear...
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| Published in | Bioinformatics Vol. 36; no. 4; pp. 1234 - 1240 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Oxford University Press
15.02.2020
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Abstract
Motivation
Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep learning has boosted the development of effective biomedical text mining models. However, directly applying the advancements in NLP to biomedical text mining often yields unsatisfactory results due to a word distribution shift from general domain corpora to biomedical corpora. In this article, we investigate how the recently introduced pre-trained language model BERT can be adapted for biomedical corpora.
Results
We introduce BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining), which is a domain-specific language representation model pre-trained on large-scale biomedical corpora. With almost the same architecture across tasks, BioBERT largely outperforms BERT and previous state-of-the-art models in a variety of biomedical text mining tasks when pre-trained on biomedical corpora. While BERT obtains performance comparable to that of previous state-of-the-art models, BioBERT significantly outperforms them on the following three representative biomedical text mining tasks: biomedical named entity recognition (0.62% F1 score improvement), biomedical relation extraction (2.80% F1 score improvement) and biomedical question answering (12.24% MRR improvement). Our analysis results show that pre-training BERT on biomedical corpora helps it to understand complex biomedical texts.
Availability and implementation
We make the pre-trained weights of BioBERT freely available at https://github.com/naver/biobert-pretrained, and the source code for fine-tuning BioBERT available at https://github.com/dmis-lab/biobert. |
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| AbstractList | Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep learning has boosted the development of effective biomedical text mining models. However, directly applying the advancements in NLP to biomedical text mining often yields unsatisfactory results due to a word distribution shift from general domain corpora to biomedical corpora. In this article, we investigate how the recently introduced pre-trained language model BERT can be adapted for biomedical corpora.MOTIVATIONBiomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep learning has boosted the development of effective biomedical text mining models. However, directly applying the advancements in NLP to biomedical text mining often yields unsatisfactory results due to a word distribution shift from general domain corpora to biomedical corpora. In this article, we investigate how the recently introduced pre-trained language model BERT can be adapted for biomedical corpora.We introduce BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining), which is a domain-specific language representation model pre-trained on large-scale biomedical corpora. With almost the same architecture across tasks, BioBERT largely outperforms BERT and previous state-of-the-art models in a variety of biomedical text mining tasks when pre-trained on biomedical corpora. While BERT obtains performance comparable to that of previous state-of-the-art models, BioBERT significantly outperforms them on the following three representative biomedical text mining tasks: biomedical named entity recognition (0.62% F1 score improvement), biomedical relation extraction (2.80% F1 score improvement) and biomedical question answering (12.24% MRR improvement). Our analysis results show that pre-training BERT on biomedical corpora helps it to understand complex biomedical texts.RESULTSWe introduce BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining), which is a domain-specific language representation model pre-trained on large-scale biomedical corpora. With almost the same architecture across tasks, BioBERT largely outperforms BERT and previous state-of-the-art models in a variety of biomedical text mining tasks when pre-trained on biomedical corpora. While BERT obtains performance comparable to that of previous state-of-the-art models, BioBERT significantly outperforms them on the following three representative biomedical text mining tasks: biomedical named entity recognition (0.62% F1 score improvement), biomedical relation extraction (2.80% F1 score improvement) and biomedical question answering (12.24% MRR improvement). Our analysis results show that pre-training BERT on biomedical corpora helps it to understand complex biomedical texts.We make the pre-trained weights of BioBERT freely available at https://github.com/naver/biobert-pretrained, and the source code for fine-tuning BioBERT available at https://github.com/dmis-lab/biobert.AVAILABILITY AND IMPLEMENTATIONWe make the pre-trained weights of BioBERT freely available at https://github.com/naver/biobert-pretrained, and the source code for fine-tuning BioBERT available at https://github.com/dmis-lab/biobert. Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep learning has boosted the development of effective biomedical text mining models. However, directly applying the advancements in NLP to biomedical text mining often yields unsatisfactory results due to a word distribution shift from general domain corpora to biomedical corpora. In this article, we investigate how the recently introduced pre-trained language model BERT can be adapted for biomedical corpora. We introduce BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining), which is a domain-specific language representation model pre-trained on large-scale biomedical corpora. With almost the same architecture across tasks, BioBERT largely outperforms BERT and previous state-of-the-art models in a variety of biomedical text mining tasks when pre-trained on biomedical corpora. While BERT obtains performance comparable to that of previous state-of-the-art models, BioBERT significantly outperforms them on the following three representative biomedical text mining tasks: biomedical named entity recognition (0.62% F1 score improvement), biomedical relation extraction (2.80% F1 score improvement) and biomedical question answering (12.24% MRR improvement). Our analysis results show that pre-training BERT on biomedical corpora helps it to understand complex biomedical texts. We make the pre-trained weights of BioBERT freely available at https://github.com/naver/biobert-pretrained, and the source code for fine-tuning BioBERT available at https://github.com/dmis-lab/biobert. Abstract Motivation Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing (NLP), extracting valuable information from biomedical literature has gained popularity among researchers, and deep learning has boosted the development of effective biomedical text mining models. However, directly applying the advancements in NLP to biomedical text mining often yields unsatisfactory results due to a word distribution shift from general domain corpora to biomedical corpora. In this article, we investigate how the recently introduced pre-trained language model BERT can be adapted for biomedical corpora. Results We introduce BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining), which is a domain-specific language representation model pre-trained on large-scale biomedical corpora. With almost the same architecture across tasks, BioBERT largely outperforms BERT and previous state-of-the-art models in a variety of biomedical text mining tasks when pre-trained on biomedical corpora. While BERT obtains performance comparable to that of previous state-of-the-art models, BioBERT significantly outperforms them on the following three representative biomedical text mining tasks: biomedical named entity recognition (0.62% F1 score improvement), biomedical relation extraction (2.80% F1 score improvement) and biomedical question answering (12.24% MRR improvement). Our analysis results show that pre-training BERT on biomedical corpora helps it to understand complex biomedical texts. Availability and implementation We make the pre-trained weights of BioBERT freely available at https://github.com/naver/biobert-pretrained, and the source code for fine-tuning BioBERT available at https://github.com/dmis-lab/biobert. |
| Author | Lee, Jinhyuk Kim, Sungdong Kim, Donghyeon Kim, Sunkyu So, Chan Ho Yoon, Wonjin Kang, Jaewoo |
| AuthorAffiliation | 2 Clova AI Research, Naver Corp , Seong-Nam 13561, Korea 1 Department of Computer Science and Engineering, Korea University , Seoul 02841, Korea 3 Interdisciplinary Graduate Program in Bioinformatics, Korea University , Seoul 02841, Korea |
| AuthorAffiliation_xml | – name: 3 Interdisciplinary Graduate Program in Bioinformatics, Korea University , Seoul 02841, Korea – name: 2 Clova AI Research, Naver Corp , Seong-Nam 13561, Korea – name: 1 Department of Computer Science and Engineering, Korea University , Seoul 02841, Korea |
| Author_xml | – sequence: 1 givenname: Jinhyuk orcidid: 0000-0003-4972-239X surname: Lee fullname: Lee, Jinhyuk organization: Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea – sequence: 2 givenname: Wonjin orcidid: 0000-0002-6435-548X surname: Yoon fullname: Yoon, Wonjin organization: Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea – sequence: 3 givenname: Sungdong orcidid: 0000-0002-0240-6210 surname: Kim fullname: Kim, Sungdong organization: Clova AI Research, Naver Corp, Seong-Nam 13561, Korea – sequence: 4 givenname: Donghyeon orcidid: 0000-0002-8224-8354 surname: Kim fullname: Kim, Donghyeon organization: Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea – sequence: 5 givenname: Sunkyu orcidid: 0000-0002-0240-6210 surname: Kim fullname: Kim, Sunkyu organization: Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea – sequence: 6 givenname: Chan Ho orcidid: 0000-0001-7633-1074 surname: So fullname: So, Chan Ho organization: Interdisciplinary Graduate Program in Bioinformatics, Korea University, Seoul 02841, Korea – sequence: 7 givenname: Jaewoo orcidid: 0000-0001-6798-9106 surname: Kang fullname: Kang, Jaewoo email: kangj@korea.ac.kr organization: Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31501885$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.18653/v1/W19-1908 10.1371/journal.pone.0065390 10.18653/v1/W19-1909 10.1016/j.compbiomed.2019.04.002 10.1186/s12859-019-2813-6 10.1093/bioinformatics/btx172 10.1186/s12859-015-0472-9 10.1016/j.jbi.2012.04.004 10.1136/amiajnl-2011-000203 10.1093/bioinformatics/btx761 10.1186/gb-2008-9-s2-s2 10.1186/1471-2105-11-85 10.1093/bioinformatics/bty449 10.1016/j.jbi.2013.12.006 10.1186/s12859-015-0564-6 10.1371/journal.pone.0200699 10.1186/1758-2946-7-S1-S2 10.3115/v1/D14-1162 10.1093/database/bay060 10.1093/bioinformatics/btx228 |
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| References | Doğan (2023013110145762300_btz682-B5) 2014; 47 Pennington (2023013110145762300_btz682-B21) 2014 Mohan (2023013110145762300_btz682-B19) 2019 Uzuner (2023013110145762300_btz682-B30) 2011; 18 Lou (2023013110145762300_btz682-B15) 2017; 33 Sousa (2023013110145762300_btz682-B27) 2019 Krallinger (2023013110145762300_btz682-B10) 2015; 7 Habibi (2023013110145762300_btz682-B8) 2017; 33 Wu (2023013110145762300_btz682-B35) 2016 Li (2023013110145762300_btz682-B12) 2016; 2016 Kim (2023013110145762300_btz682-B9) 2004 McCann (2023013110145762300_btz682-B17) 2017 Bravo (2023013110145762300_btz682-B3) 2015; 16 Giorgi (2023013110145762300_btz682-B7) 2018; 34 Lim (2023013110145762300_btz682-B13) 2018; 2018 Van Mulligen (2023013110145762300_btz682-B31) 2012; 45 Wiese (2023013110145762300_btz682-B34) 2017 Wang (2023013110145762300_btz682-B33) 2018 Devlin (2023013110145762300_btz682-B4) 2019 Sachan (2023013110145762300_btz682-B25) 2018 Xu (2023013110145762300_btz682-B36) 2019; 108 Yoon (2023013110145762300_btz682-B37) 2019; 20 Mikolov (2023013110145762300_btz682-B18) 2013 Pafilis (2023013110145762300_btz682-B20) 2013; 8 Peters (2023013110145762300_btz682-B22) 2018 Rajpurkar (2023013110145762300_btz682-B24) 2016 Sung (2023013110145762300_btz682-B28) 2017 Smith (2023013110145762300_btz682-B26) 2008; 9 Tsatsaronis (2023013110145762300_btz682-B29) 2015; 16 Pyysalo (2023013110145762300_btz682-B23) 2013 Krallinger (2023013110145762300_btz682-B11) 2017 Zhu (2023013110145762300_btz682-B38) 2018 Alsentzer (2023013110145762300_btz682-B1) 2019 Vaswani (2023013110145762300_btz682-B32) 2017 Bhasuran (2023013110145762300_btz682-B2) 2018; 13 Gerner (2023013110145762300_btz682-B6) 2010; 11 Luo (2023013110145762300_btz682-B16) 2018; 34 Lin (2023013110145762300_btz682-B14) 2019 |
| References_xml | – start-page: 65 year: 2019 ident: 2023013110145762300_btz682-B14 article-title: A bert-based universal model for both within-and cross-sentence clinical temporal relation extraction publication-title: Proceedings of the 2nd Clinical Natural Language Processing Workshop, Minneapolis, MN, USA. doi: 10.18653/v1/W19-1908 – volume: 8 start-page: e65390 year: 2013 ident: 2023013110145762300_btz682-B20 article-title: The species and organisms resources for fast and accurate identification of taxonomic names in text publication-title: PLoS One doi: 10.1371/journal.pone.0065390 – start-page: 72 year: 2019 ident: 2023013110145762300_btz682-B1 article-title: Publicly available clinical bert embeddings publication-title: Proceedings of the 2nd Clinical Natural Language Processing Workshop, Minneapolis, MN, USA doi: 10.18653/v1/W19-1909 – year: 2018 ident: 2023013110145762300_btz682-B38 – volume: 108 start-page: 122 year: 2019 ident: 2023013110145762300_btz682-B36 article-title: Document-level attention-based BiLSTM-CRF incorporating disease dictionary for disease named entity recognition publication-title: Comput. Biol. Med doi: 10.1016/j.compbiomed.2019.04.002 – volume: 20 start-page: 249 year: 2019 ident: 2023013110145762300_btz682-B37 article-title: Collabonet: collaboration of deep neural networks for biomedical named entity recognition publication-title: BMC Bioinformatics doi: 10.1186/s12859-019-2813-6 – volume: 33 start-page: 2363 year: 2017 ident: 2023013110145762300_btz682-B15 article-title: A transition-based joint model for disease named entity recognition and normalization publication-title: Bioinformatics doi: 10.1093/bioinformatics/btx172 – volume: 16 start-page: 55 year: 2015 ident: 2023013110145762300_btz682-B3 article-title: Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research publication-title: BMC Bioinformatics doi: 10.1186/s12859-015-0472-9 – start-page: 3111 year: 2013 ident: 2023013110145762300_btz682-B18 article-title: Distributed representations of words and phrases and their compositionality publication-title: Advances in Neural Information Processing Systems 26 – volume: 45 start-page: 879 year: 2012 ident: 2023013110145762300_btz682-B31 article-title: The EU-ADR corpus: annotated drugs, diseases, targets, and their relationships publication-title: J. Biomed. Inform doi: 10.1016/j.jbi.2012.04.004 – year: 2004 ident: 2023013110145762300_btz682-B9 – start-page: 4171 year: 2019 ident: 2023013110145762300_btz682-B4 article-title: Bert: pre-training of deep bidirectional transformers for language understanding publication-title: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, MN, USA – year: 2018 ident: 2023013110145762300_btz682-B22 – volume: 18 start-page: 552 year: 2011 ident: 2023013110145762300_btz682-B30 article-title: 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text publication-title: J. Am. Med. Inform. Assoc doi: 10.1136/amiajnl-2011-000203 – year: 2019 ident: 2023013110145762300_btz682-B19 – year: 2016 ident: 2023013110145762300_btz682-B24 – volume: 2016 year: 2016 ident: 2023013110145762300_btz682-B12 article-title: Biocreative V CDR task corpus: a resource for chemical disease relation extraction publication-title: Database – volume: 34 start-page: 1381 year: 2018 ident: 2023013110145762300_btz682-B16 article-title: An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition publication-title: Bioinformatics doi: 10.1093/bioinformatics/btx761 – volume: 9 start-page: S2 year: 2008 ident: 2023013110145762300_btz682-B26 article-title: Overview of biocreative ii gene mention recognition publication-title: Genome Biol doi: 10.1186/gb-2008-9-s2-s2 – year: 2017 ident: 2023013110145762300_btz682-B34 – start-page: 141 year: 2017 ident: 2023013110145762300_btz682-B11 article-title: Overview of the BioCreative VI chemical-protein interaction track publication-title: Proceedings of the BioCreative VI Workshop, Bethesda, MD, USA – start-page: 6294 year: 2017 ident: 2023013110145762300_btz682-B17 article-title: Learned in translation: contextualized word vectors publication-title: Advances in Neural Information Processing Systems 30 – start-page: 1487 year: 2019 ident: 2023013110145762300_btz682-B27 article-title: A silver standard corpus of human phenotype-gene relations publication-title: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Minneapolis, MN – volume: 11 start-page: 85 year: 2010 ident: 2023013110145762300_btz682-B6 article-title: Linnaeus: a species name identification system for biomedical literature publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-11-85 – start-page: 5998 year: 2017 ident: 2023013110145762300_btz682-B32 article-title: Attention is all you need publication-title: Advances in Neural Information Processing Systems – volume: 34 start-page: 4087 year: 2018 ident: 2023013110145762300_btz682-B7 article-title: Transfer learning for biomedical named entity recognition with neural networks publication-title: Bioinformatics doi: 10.1093/bioinformatics/bty449 – year: 2017 ident: 2023013110145762300_btz682-B28 – volume: 47 start-page: 1 year: 2014 ident: 2023013110145762300_btz682-B5 article-title: NCBI disease corpus: a resource for disease name recognition and concept normalization publication-title: J. Biomed. Inform doi: 10.1016/j.jbi.2013.12.006 – start-page: 39 year: 2013 ident: 2023013110145762300_btz682-B23 article-title: Distributional semantics resources for biomedical text processing publication-title: Proceedings of the 5th International Symposium on Languages in Biology and Medicine, Tokyo, Japan – volume: 16 start-page: 138 year: 2015 ident: 2023013110145762300_btz682-B29 article-title: An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition publication-title: BMC Bioinformatics doi: 10.1186/s12859-015-0564-6 – volume: 13 start-page: e0200699 year: 2018 ident: 2023013110145762300_btz682-B2 article-title: Automatic extraction of gene-disease associations from literature using joint ensemble learning publication-title: PLoS One doi: 10.1371/journal.pone.0200699 – volume: 7 year: 2015 ident: 2023013110145762300_btz682-B10 article-title: The chemdner corpus of chemicals and drugs and its annotation principles publication-title: J. Cheminform doi: 10.1186/1758-2946-7-S1-S2 – start-page: 1532 year: 2014 ident: 2023013110145762300_btz682-B21 article-title: Glove: Global vectors for word representation publication-title: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar doi: 10.3115/v1/D14-1162 – year: 2018 ident: 2023013110145762300_btz682-B33 – year: 2016 ident: 2023013110145762300_btz682-B35 – volume: 2018 year: 2018 ident: 2023013110145762300_btz682-B13 article-title: Chemical–gene relation extraction using recursive neural network publication-title: Database doi: 10.1093/database/bay060 – volume: 33 start-page: i37 year: 2017 ident: 2023013110145762300_btz682-B8 article-title: Deep learning with word embeddings improves biomedical named entity recognition publication-title: Bioinformatics doi: 10.1093/bioinformatics/btx228 – year: 2018 ident: 2023013110145762300_btz682-B25 |
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Motivation
Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural... Biomedical text mining is becoming increasingly important as the number of biomedical documents rapidly grows. With the progress in natural language processing... |
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| Title | BioBERT: a pre-trained biomedical language representation model for biomedical text mining |
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