Biomedical Relation Extraction Using Dependency Graph and Decoder-Enhanced Transformer Model.

CPR (chemical–protein relation) ChemProt DDI (drug–drug interaction) GAT (graph-attention network) T5 (text-to-text transfer transformer) relation extraction self-attention transformer

Journal

Bioengineering (Basel, Switzerland)
ISSN: 2306-5354
Titre abrégé: Bioengineering (Basel)
Pays: Switzerland
ID NLM: 101676056

Informations de publication

Date de publication:
12 May 2023
Historique:
received: 01 03 2023
revised: 06 05 2023
accepted: 09 05 2023
medline: 27 5 2023
pubmed: 27 5 2023
entrez: 27 5 2023
Statut: epublish

Résumé

The identification of drug-drug and chemical-protein interactions is essential for understanding unpredictable changes in the pharmacological effects of drugs and mechanisms of diseases and developing therapeutic drugs. In this study, we extract drug-related interactions from the DDI (Drug-Drug Interaction) Extraction-2013 Shared Task dataset and the BioCreative ChemProt (Chemical-Protein) dataset using various transfer transformers. We propose BERT

Identifiants

pubmed: 37237656
pii: bioengineering10050586
doi: 10.3390/bioengineering10050586
pmc: PMC10215465
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Korea Foundation
ID : NRF-2020R1I1A1A01073125

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Auteurs

Seonho Kim (S)

Department of Computer Science and Engineering, Sogang University, Seoul 04107, Republic of Korea.

Juntae Yoon (J)

VAIV Company, Seoul 04107, Republic of Korea.

Ohyoung Kwon (O)

Department of Future Technology, Korea University of Technology and Education, Cheonan-si 31253, Republic of Korea.

Classifications MeSH