A computational ecosystem to support eHealth Knowledge Discovery technologies in Spanish.
Annotated corpora
Entity recognition
Knowledge discovery
Natural language processing
Relation extraction
Semantic annotation models
Journal
Journal of biomedical informatics
ISSN: 1532-0480
Titre abrégé: J Biomed Inform
Pays: United States
ID NLM: 100970413
Informations de publication
Date de publication:
09 2020
09 2020
Historique:
received:
05
03
2020
revised:
18
05
2020
accepted:
19
07
2020
pubmed:
28
7
2020
medline:
29
7
2021
entrez:
27
7
2020
Statut:
ppublish
Résumé
The massive amount of biomedical information published online requires the development of automatic knowledge discovery technologies to effectively make use of this available content. To foster and support this, the research community creates linguistic resources, such as annotated corpora, and designs shared evaluation campaigns and academic competitive challenges. This work describes an ecosystem that facilitates research and development in knowledge discovery in the biomedical domain, specifically in Spanish language. To this end, several resources are developed and shared with the research community, including a novel semantic annotation model, an annotated corpus of 1045 sentences, and computational resources to build and evaluate automatic knowledge discovery techniques. Furthermore, a research task is defined with objective evaluation criteria, and an online evaluation environment is setup and maintained, enabling researchers interested in this task to obtain immediate feedback and compare their results with the state-of-the-art. As a case study, we analyze the results of a competitive challenge based on these resources and provide guidelines for future research. The constructed ecosystem provides an effective learning and evaluation environment to encourage research in knowledge discovery in Spanish biomedical documents.
Identifiants
pubmed: 32712157
pii: S1532-0464(20)30145-3
doi: 10.1016/j.jbi.2020.103517
pmc: PMC7377985
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
103517Informations de copyright
Copyright © 2020 Elsevier Inc. All rights reserved.
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