Publicación:
Understanding and Improving Disability Identification in Medical Documents

Vista sencilla de ítem
dc.contributor.authorFabregat Marcos, Hermenegildo
dc.contributor.authorMartínez Romo, Juan
dc.contributor.authorAraujo Serna, M. Lourdes
dc.date.accessioned2024-06-11T15:15:29Z
dc.date.available2024-06-11T15:15:29Z
dc.date.issued2020
dc.description.abstractDisabilities are a problem that affects a large number of people in the world. Gathering information about them is crucial to improve the daily life of the people who suffer from them but, since disabilities are often strongly associated with different types of diseases, the available data are widely dispersed. In this work we review existing proposal for the problem, making an in-depth analysis, and from it we make a proposal that improves the results of previous systems. The analysis focuses on the results of the participants in DIANN shared task was proposed (IberEval 2018), devoted to the detection of named disabilities in electronic documents. In order to evaluate the proposed systems using a common evaluation framework, a corpus of documents, in both English and Spanish, was gathered and annotated. Several teams participated in the task, either using classic methods or proposing specific approaches to deal effectively with the complexities of the task. Our aim is to provide insight for future advances in the field by analyzing the participating systems and identifying the most effective approaches and elements to tackle the problem. We have validated the lessons learned from this analysis through a new proposal that includes the most promising elements used by the participating teams. The proposed system improves, for both languages, the results obtained during the task.en
dc.description.versionversión publicada
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2020.3019178
dc.identifier.issn2169-3536
dc.identifier.urihttps://hdl.handle.net/20.500.14468/22414
dc.journal.titleIEEE Access
dc.journal.volume8
dc.language.isoen
dc.publisherIEEE
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentLenguajes y Sistemas Informáticos
dc.rightsAtribución 4.0 Internacional
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subject.keywordsdisabilities
dc.subject.keywordsbiomedical corpus
dc.subject.keywordsentity recognition
dc.subject.keywordsshared task analysis
dc.titleUnderstanding and Improving Disability Identification in Medical Documentses
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
relation.isAuthorOfPublication91b7e317-2a30-494f-98e9-3a0e026747b1
relation.isAuthorOfPublication77c4023e-4374-442a-9dfb-b9d4b609c31e
relation.isAuthorOfPublication.latestForDiscovery91b7e317-2a30-494f-98e9-3a0e026747b1
Archivos
Bloque original
Mostrando 1 - 1 de 1
Miniatura
Nombre:
Martinez-Romo_Juan_IEEEAccess2020.pdf
Tamaño:
4.23 MB
Formato:
Adobe Portable Document Format
Descargar
Colecciones
Artículos y papers