Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/213240
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Barrios, Juan Ignacio | - |
dc.contributor.author | Marsol Torrent, Sergi | - |
dc.date.accessioned | 2024-06-14T15:38:00Z | - |
dc.date.available | 2024-06-14T15:38:00Z | - |
dc.date.issued | 2024-06-05 | - |
dc.identifier.uri | http://hdl.handle.net/2445/213240 | - |
dc.description | Treballs Finals de Grau d'Enginyeria Biomèdica. Facultat de Medicina i Ciències de la Salut. Universitat de Barcelona. Curs: 2023-2024. Tutor/Director: Juan Ignacio Barrios ; Director: Luis Gascó, Martin Krallinger | ca |
dc.description.abstract | The medical sector generates vast amounts of unstructured data, which, if processed correctly, can significantly enhance medical processes and their outcomes. This thesis presents the development of KeyCARE, a Python library for keyword extraction, term categorization, and relations extraction that tackles this need. Utilizing mainly unsupervised and few-shot methods, KeyCARE efficiently extracts classified keywords from medical records with a recall of up to 98% and an f-score of up to 61%, with partial overlaps considered as correct. While these scores are not comparable to those of supervised Named Entity Recognition systems, they set a high standard for an unsupervised alternative in scenarios of data scarcity. Moreover, the library incorporates relation extractors that identify hierarchical relationships among biomedical keywords and with terminologies, achieving a precision and recall of 93%. This has a clear application in terminology enrichment, data generation and information extraction, particularly in specific domains and low-resource languages such as Catalan. This thesis encompasses the comprehensive development of KeyCARE, including an in-depth evaluation of the implemented models as well as basic use cases demonstrating its practical applications. | ca |
dc.format.extent | 76 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | ca |
dc.rights | cc-by-nc-nd (c) Sergi Marsol Torrent, 2024 | - |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.source | Treballs Finals de Grau (TFG) - Enginyeria Biomèdica | - |
dc.subject.classification | Enginyeria biomèdica | - |
dc.subject.classification | Materials biomèdics | - |
dc.subject.classification | Treballs de fi de grau | - |
dc.subject.other | Biomedical engineering | - |
dc.subject.other | Biomedical materials | - |
dc.subject.other | Bachelor's theses | - |
dc.title | KeyCARE: a framework for biomedical Keyword Extraction, term Categorization, and semantic Relation | ca |
dc.type | info:eu-repo/semantics/bachelorThesis | ca |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca |
Appears in Collections: | Treballs Finals de Grau (TFG) - Enginyeria Biomèdica |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
TFG_ Marsol_Torrent_Sergi.pdf | 3.74 MB | Adobe PDF | View/Open |
This item is licensed under a
Creative Commons License