The big data era: The usefulness of folksonomy for natural language processing

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  • dc.contributor.author Sans Atxer, Laia
  • dc.contributor.author Vallbé, Ismael
  • dc.contributor.author Teixidó, Joan
  • dc.contributor.author Picas, Josep Manel
  • dc.contributor.author Martínez Roldán, Jordi
  • dc.contributor.author Pascual Santos, Julio
  • dc.date.accessioned 2024-05-16T06:26:13Z
  • dc.date.available 2024-05-16T06:26:13Z
  • dc.date.issued 2022
  • dc.description.abstract Background: A huge amount of clinical data is generated daily and it is usually filed in clinical reports as natural language. Data extraction and further analysis requires reading and manual review of each report, which is a time consuming process. With the aim to test folksonomy to quickly obtain and analyze the information contained in media reports we set up this study. Methods and objectives: We have used folksonomy to quickly obtain and analyze data from 1631 discharge clinical reports from the Nephrology Department of Hospital del Mar, without the need to create a structured database. Results: After posing some questions related to daily clinical practice (hypoglycaemic drugs used in diabetic patients, antihypertensive drugs and the use of renin angiotensin blockers during hospitalization in the nephrology department and data related to emotional environment of patients with chronic kidney disease) this tool has allowed the conversion of unstructured information in natural language into a structured pool of data for its further analysis. Conclusions: Folksonomy allows the conversion of the information contained in clinical reports as natural language into a pool of structured data which can be further easily analyzed without the need for the classical manual review of the reports.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Sans L, Vallvé I, Teixidó J, Picas JM, Martínez-Roldán J, Pascual J. The big data era: The usefulness of folksonomy for natural language processing. Nefrologia (Engl Ed). 2022 Nov-Dec;42(6):680-7. DOI: 10.1016/j.nefroe.2023.02.007
  • dc.identifier.doi http://dx.doi.org/10.1016/j.nefroe.2023.02.007
  • dc.identifier.issn 2013-2514
  • dc.identifier.uri http://hdl.handle.net/10230/60167
  • dc.language.iso eng
  • dc.publisher Elsevier
  • dc.relation.ispartof Nefrologia (Engl Ed). 2022 Nov-Dec;42(6):680-7
  • dc.rights © 2021 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. This is an open access article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
  • dc.subject.keyword Big data
  • dc.subject.keyword Folksonomy
  • dc.subject.keyword Natural language processing
  • dc.subject.keyword Nephrology
  • dc.title The big data era: The usefulness of folksonomy for natural language processing
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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Articles (Hospital del Mar Research Institute)