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Fine-grained Certainty Level Annotations Used for Coarser-grained E-health Scenarios: Certainty Classication of Diagnostic Statements in Swedish Clinical Text
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2012 (English)In: Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part II / [ed] Alexander Gelbukh, Berlin/Heidelberg: Springer Berlin/Heidelberg, 2012, 450-461 p.Conference paper, Published paper (Refereed)
Abstract [en]

An important task in information access methods is distinguishingfactual information from speculative or negated information.Fine-grained certainty levels of diagnostic statements in Swedish clinicaltext are annotated in a corpus from a medical university hospital.The annotation model has two polarities (positive and negative) andthree certainty levels. However, there are many e-health scenarios wheresuch ne-grained certainty levels are not practical for information extraction.Instead, more coarse-grained groups are needed. We presentthree scenarios: adverse event surveillance, decision support alerts andautomatic summaries and collapse the ne-grained certainty level classi-cations into coarser-grained groups. We build automatic classiers foreach scenario and analyze the results quantitatively. Annotation discrepanciesare analyzed qualitatively through manual corpus analysis. Ourmain ndings are that it is feasible to use a corpus of ne-grained certaintylevel annotations to build classiers for coarser-grained real-worldscenarios: 0.89, 0.91 and 0.8 F-score (overall average).

Place, publisher, year, edition, pages
Berlin/Heidelberg: Springer Berlin/Heidelberg, 2012. 450-461 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 7192
Keyword [en]
Clinical documentation, Certainty level classication, Annotation granularity, Automatic Summary, Decision Support Alerts, Adverse Event Surveillance, E-health
National Category
Information Systems, Social aspects
Research subject
Computer Science; IT for health
Identifiers
URN: urn:nbn:se:su:diva-74810DOI: 10.1007/978-3-642-28601-8_38ISBN: 978-3-642-28600-1 (print)OAI: oai:DiVA.org:su-74810DiVA: diva2:512161
Conference
CICLing 2012, New Delhi, India, March 11–17, 2012
Available from: 2012-03-26 Created: 2012-03-26 Last updated: 2013-02-07Bibliographically approved
In thesis
1. Shades of Certainty: Annotation and Classification of Swedish Medical Records
Open this publication in new window or tab >>Shades of Certainty: Annotation and Classification of Swedish Medical Records
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Access to information is fundamental in health care. This thesis presents research on Swedish medical records with the overall goal of building intelligent information access tools that can aid health personnel, researchers and other professions in their daily work, and, ultimately, improve health care in general.

The issue of ethics and identifiable information is addressed by creating an annotated gold standard corpus and porting an existing de-identification system to Swedish from English. The aim is to move towards making textual resources available to researchers without risking exposure of patients’ confidential information. Results for the rule-based system are not encouraging, but results for the gold standard are fairly high.

Affirmed, uncertain and negated information needs to be distinguished when building accurate information extraction tools. Annotation models are created, with the aim of building automated systems. One model distinguishes certain and uncertain sentences, and is applied on medical records from several clinical departments. In a second model, two polarities and three levels of certainty are applied on diagnostic statements from an emergency department. Overall results are promising. Differences are seen depending on clinical practice, annotation task and level of domain expertise among the annotators.

Using annotated resources for automatic classification is studied. Encouraging overall results using local context information are obtained. The fine-grained certainty levels are used for building classifiers for real-world e-health scenarios.

This thesis contributes two annotation models of certainty and one of identifiable information, applied on Swedish medical records. A deeper understanding of the language use linked to conveying certainty levels is gained. Three annotated resources that can be used for further research have been created, and implications for automated systems are presented.

Place, publisher, year, edition, pages
Stockholm: Department of Computer and Systems Sciences, Stockholm University, 2012. 78 p.
Series
Report Series / Department of Computer & Systems Sciences, ISSN 1101-8526 ; 12-002
Keyword
Clinical documentation, Certainty level classification, Annotation, E-health, Corpus creation, De-identification, Speculative language, Medical Records, Swedish, Natural Language Processing, Language Technology
National Category
Information Systems, Social aspects
Research subject
Computer and Systems Sciences
Identifiers
urn:nbn:se:su:diva-74828 (URN)978-91-7447-444-2 (ISBN)
Public defence
2012-04-27, Sal C, Forum 100, Isafjordsgatan 39, Kista, 13:00 (English)
Opponent
Supervisors
Available from: 2012-04-05 Created: 2012-03-27 Last updated: 2012-03-28Bibliographically approved

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Citation style
  • apa
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More styles
Language
  • de-DE
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  • fi-FI
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  • nn-NB
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  • Other locale
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Output format
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  • text
  • asciidoc
  • rtf