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Identifying suicidal adolescents from mental health records using natural language processing
KTH, School of Electrical Engineering and Computer Science (EECS), Theoretical Computer Science, TCS. King's College London, London, United Kingdom.ORCID iD: 0000-0002-4178-2980
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2019 (English)In: 17th World Congress on Medical and Health Informatics, MEDINFO 2019, IOS Press, 2019, Vol. 264, p. 413-417Conference paper, Published paper (Refereed)
Abstract [en]

Suicidal ideation is a risk factor for self-harm, completed suicide and can be indicative of mental health issues. Adolescents are a particularly vulnerable group, but few studies have examined suicidal behaviour prevalence in large cohorts. Electronic Health Records (EHRs) are a rich source of secondary health care data that could be used to estimate prevalence. Most EHR documentation related to suicide risk is written in free text, thus requiring Natural Language Processing (NLP) approaches. We adapted and evaluated a simple lexicon- and rule-based NLP approach to identify suicidal adolescents from a large EHR database. We developed a comprehensive manually annotated EHR reference standard and assessed NLP performance at both document and patient level on data from 200 patients (~5000 documents). We achieved promising results (>80% f1 score at both document and patient level). Simple NLP approaches can be successfully used to identify patients who exhibit suicidal risk behaviour, and our proposed approach could be useful for other populations and settings.

Place, publisher, year, edition, pages
IOS Press, 2019. Vol. 264, p. 413-417
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 264
Keywords [en]
Electronic Health Records, Natural Language Processing, Suicide
National Category
Other Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-262522DOI: 10.3233/SHTI190254Scopus ID: 2-s2.0-85071484866ISBN: 9781643680026 (print)OAI: oai:DiVA.org:kth-262522DiVA, id: diva2:1366086
Conference
17th World Congress on Medical and Health Informatics, MEDINFO 2019; Lyon; France; 25 August 2019 through 30 August 2019
Note

QC 20191028

Available from: 2019-10-28 Created: 2019-10-28 Last updated: 2019-10-28Bibliographically approved

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Velupillai, Sumithra

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CiteExportLink to record
Permanent link

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