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Annotating temporal relations to determine the onset of psychosis symptoms
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2019 (English)In: 17th World Congress on Medical and Health Informatics, MEDINFO 2019, IOS Press, 2019, p. 418-422Conference paper, Published paper (Refereed)
Abstract [en]

For patients with a diagnosis of schizophrenia, determining symptom onset is crucial for timely and successful intervention. In mental health records, information about early symptoms is often documented only in free text, and thus needs to be extracted to support clinical research. To achieve this, natural language processing (NLP) methods can be used. Development and evaluation of NLP systems requires manually annotated corpora. We present a corpus of mental health records annotated with temporal relations for psychosis symptoms. We propose a methodology for document selection and manual annotation to detect symptom onset information, and develop an annotated corpus. To assess the utility of the created corpus, we propose a pilot NLP system. To the best of our knowledge, this is the first temporally-annotated corpus tailored to a specific clinical use-case.

Place, publisher, year, edition, pages
IOS Press, 2019. p. 418-422
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 264
Keywords [en]
Electronic Health Records, Natural Language Processing, Schizophrenia
National Category
Other Health Sciences
Identifiers
URN: urn:nbn:se:kth:diva-262523DOI: 10.3233/SHTI190255Scopus ID: 2-s2.0-85071455534ISBN: 9781643680026 (print)OAI: oai:DiVA.org:kth-262523DiVA, id: diva2:1366083
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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Citation style
  • apa
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Language
  • de-DE
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  • fi-FI
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  • nn-NB
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Output format
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