Retrieving disorders and ﬁndings: Results using SNOMED CT and NegEx adapted for Swedish
2011 (English)In: LOUHI 2011 Health Document Text Mining and Information Analysis 2011: Proceedings of LOUHI 2011 Third International Workshop on Health Document Text Mining and Information AnalysisBled, Slovenia, July 6, 2011. / [ed] Øystein Nytrø, Laura Slaughter, Hans Moen, 2011, 11-17 p.Conference paper (Other academic)
Access to reliable data from electronic health records is of high importance in several key areas in patient care, biomedical research, and education. However, many of the clinical entities are negated in the patient record text. Detecting what is a negation and what is not is therefore a key to high quality text mining. In this study we used the NegEx system adapted for Swedish to investigate negated clinical entities. We applied the system to a subset of free-text entries under a heading containing the word ‘assessment’ from the Stockholm EPR corpus, containing in total 23,171,559 tokens. Speciﬁcally, the explored entities were the SNOMED CT terms having the semantic categories ‘ﬁnding’ or ‘disorder’. The study showed that the proportion of negated clinical entities was around 9%. The results thus support that negations are abundant in clinical text and hence negation detection is vital for high quality text mining in the medical domain.
Place, publisher, year, edition, pages
2011. 11-17 p.
, CEUR Workshop Proceedings, ISSN 1613-0073 ; 744
Negation detection, Clinical text, Electronic patient records, SNOMED CT, Swedish
Negationsdetektion, Klinisk text, Elektroniska patientjournaler, SNOMED CT, Svenska
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-62354OAI: oai:DiVA.org:su-62354DiVA: diva2:441279
Third International Workshop on Health Document Text Mining and Information AnalysisBled, Slovenia, July 6, 2011, Bled Slovenia, Collocated with AIME 2011.