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Rough Set Theory in the Classification of Diagnoses
Responsible organisation
2009 (English)In: Computers in Medical Activity. Series: Advances in Intelligent and Soft Computing / [ed] E., Kacki; M., Rudnicki; J., Stempczynska, Berlin Heidelberg: Springer-Verlag , 2009, 41-52 p.Chapter in book (Refereed)
Abstract [en]

Rough sets, surrounded by two approximation sets filled with sure and possible members constitute perfect mathematical tools of the classification of some objects. In this work we adopt the rough technique to verify diagnostic decisions concerning a sample of patients whose symptoms are typical of a considered diagnosis. The objective is to extract the patients who surely suffer from the diagnosis, to indicate the patients who are free from it, and even to make decisions in undefined diagnostic cases. By applying selected logical decision rules, we also discuss a possibility of reducing of symptom sets to their minimal collections preserving the previous results in order to minimize a number of numerical calculations.

Place, publisher, year, edition, pages
Berlin Heidelberg: Springer-Verlag , 2009. 41-52 p.
National Category
Mathematics Medical and Health Sciences
Identifiers
URN: urn:nbn:se:bth-7929Local ID: oai:bth.se:forskinfoEBE9FE19C9A4C35EC1257684005AD7F6ISBN: 978-3-642-04461-8 (print)OAI: oai:DiVA.org:bth-7929DiVA: diva2:835604
Available from: 2012-09-18 Created: 2009-12-06 Last updated: 2016-09-20Bibliographically approved

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  • apa
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