<div class="csl-bib-body">
<div class="csl-entry">Ningtyas, A. M. (2022). Medical Entity Linking in Laypersons’ Language. In <i>Advances in Information Retrieval</i> (pp. 513–519). Springer-Verlag. https://doi.org/10.1007/978-3-030-99739-7_63</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/142560
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dc.description.abstract
Due to the vast amount of health-related data on the Internet, a trend toward digital health literacy is emerging among laypersons. We hypothesize that providing trustworthy explanations of informal medical terms in social media can improve information quality. Entity linking (EL) is the task of associating terms with concepts (entities) in the knowledge base. The challenge with EL in lay medical texts is that the source texts are often written in loose and informal language. We propose an end-to-end entity linking approach that involves identifying informal medical terms, normalizing medical concepts according to SNOMED-CT, and linking entities to Wikipedia to provide explanations for laypersons.
en
dc.language.iso
en
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dc.relation.ispartofseries
Lecture Notes in Computer Science
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dc.subject
Named entity recognition
en
dc.subject
Medical entity linking
en
dc.subject
Medical concept normalization
en
dc.title
Medical Entity Linking in Laypersons’ Language
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.isbn
978-3-030-99738-0
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dc.description.startpage
513
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dc.description.endpage
519
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dc.type.category
Full-Paper Contribution
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dc.relation.eissn
1611-3349
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tuw.booktitle
Advances in Information Retrieval
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tuw.container.volume
13186
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tuw.peerreviewed
true
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tuw.relation.publisher
Springer-Verlag
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tuw.relation.publisherplace
Berlin, Heidelberg
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tuw.researchTopic.id
C5
-
tuw.researchTopic.name
Computer Science Foundations
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tuw.researchTopic.value
100
-
tuw.publication.orgunit
E194-04 - Forschungsbereich Data Science
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tuw.publisher.doi
10.1007/978-3-030-99739-7_63
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dc.description.numberOfPages
7
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tuw.event.name
44th European Conference on Information Retrieval (ECIR 2022)
en
tuw.event.startdate
10-04-2022
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tuw.event.enddate
14-04-2022
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tuw.event.online
Hybrid
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tuw.event.type
Event for scientific audience
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tuw.event.place
Stavanger
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tuw.event.country
NO
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tuw.event.presenter
Ningtyas, Annisa Maulida
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wb.sciencebranch
Informatik
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wb.sciencebranch
Wirtschaftswissenschaften
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
5020
-
wb.sciencebranch.value
90
-
wb.sciencebranch.value
10
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item.languageiso639-1
en
-
item.openairetype
conference paper
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item.grantfulltext
restricted
-
item.fulltext
no Fulltext
-
item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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crisitem.author.dept
E194-04 - Forschungsbereich Data Science
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crisitem.author.parentorg
E194 - Institut für Information Systems Engineering