Combining word embeddings to extract chemical and drug entities in biomedical literature

Combining word embeddings to extract chemical and drug entities in biomedical literature

Abstract Background Natural language processing (NLP) and text mining technologies for the extraction and indexing of chemical and drug entities are key to improving the access and integration of information from unstructured data such as biomedical literature. Methods In this paper we evaluate two...

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Bibliographic Details
Main Authors: Pilar López-Úbeda, Manuel Carlos Díaz-Galiano, L. Alfonso Ureña-López, M. Teresa Martín-Valdivia
Format: Article
Language:English
Published: BMC 2021-12-01
Series:BMC Bioinformatics
Subjects:
Natural language processing
Named entity recognition
Concept indexing
Neural network
Word embeddings
SNOMED-CT
Online Access:https://doi.org/10.1186/s12859-021-04188-3

Internet

https://doi.org/10.1186/s12859-021-04188-3

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