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Pathology text mining - on Norwegian prostate cancer reports
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2016 (English)In: 2016 IEEE 32nd International Conference on Data Engineering Workshops (ICDEW): Proceedings, IEEE Computer Society, 2016, 84-87 p.Conference paper, Published paper (Refereed)
Abstract [en]

Pathology reports are written by pathologists, skilled physicians, that know how to interpret disorders in various tissue samples from the human body. To obtain valuable statistics on outcome of disorders, as for example cancer and effect of treatment, statistics are collected. Therefore, cancer pathology reports interpreted and coded into databases at cancer registries. In Norway is this task carried out by the Cancer Registry of Norway (Kreftregisteret) by 25 different human coders. There is a need to automate this process. The authors of this article received 25 prostate cancer pathology reports written in Norwegian from the Cancer Registry of Norway, each documenting various stages of prostate cancer and the corresponding correct manual coding. A rule-based algorithm was produced that processed the reports in order to prototype automation. The output of the algorithm was compared to the output of the manual coding. The evaluation showed an average F-Score of 0.94 on four of these data points namely Total Malign, Primary Gleason, Secondary Gleason and Total Gleason and a lower result with on average F-score of 0.76 on all ten data points. The results are in line with previous research.

Place, publisher, year, edition, pages
IEEE Computer Society, 2016. 84-87 p.
Keyword [en]
Clinical text mining, rule based, pathology reports, prostate cancer, Norwegian
National Category
Information Systems
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-136597DOI: 10.1109/ICDEW.2016.7495622ISBN: 978-1-5090-2109-3 (electronic)OAI: oai:DiVA.org:su-136597DiVA: diva2:1055462
Conference
32nd IEEE International Conference on Data Engineering, Helsinki, Finland, May 16-20, 2016
Available from: 2016-12-12 Created: 2016-12-12 Last updated: 2017-02-09Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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  • Other style
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  • de-DE
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  • nn-NO
  • nn-NB
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Output format
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