Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Vocabulary Development To Support Information Extraction of Substance Abuse from Psychiatry Notest
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0002-4178-2980
Show others and affiliations
2016 (English)In: Proceedings of BioNLP 2016, Association for Computational Linguistics , 2016, 92-101 p.Conference paper, Published paper (Refereed)
Abstract [en]

Extracting information from mental health records can be useful for large-scale clinical studies (e.g., to predict medication adherence or to understand medication effects) in this clinical specialty largely underserved by the Natural Language Processing (NLP) community. Vocabularies that contain medical terms for specific clinical use-cases, such as signs, symptoms, histories, social risk factors, are valuable resources for the development of NLP systems that aid clinicians in extracting information from text. Substance abuse is an important variable for many clinical use-cases, but, to our knowledge, there are no publicly available vocabularies that cover these types of terms. In this study, we apply and combine three methods for generating vocabularies related to substance abuse. We propose a simple and systematic method to generate highly relevant vocabularies and evaluate these vocabularies with respect to size and content, as well as coverage and relevance when applied to authentic psychiatric notes.

Place, publisher, year, edition, pages
Association for Computational Linguistics , 2016. 92-101 p.
National Category
Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-204777OAI: oai:DiVA.org:kth-204777DiVA: diva2:1086113
Conference
BioNLP 2016,Berlin, Germany, August 12, 2016
Note

QC 20170410

Available from: 2017-03-31 Created: 2017-03-31 Last updated: 2017-04-10Bibliographically approved

Open Access in DiVA

No full text

Other links

http://www.aclweb.org/anthology/W/W16/W16-2912.pdf

Search in DiVA

By author/editor
Velupillai, Sumithra
By organisation
Theoretical Computer Science, TCS
Language Technology (Computational Linguistics)

Search outside of DiVA

GoogleGoogle Scholar

Total: 7 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf