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Rough Set Theory in the Classification of Diagnoses
Responsible organisation
2007 (English)Conference paper, (Refereed) Published
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
Lodz, Poland: The College of Computers Science , 2007.
Keyword [en]
Rough sets, lower and upper approximation, classification, reducts as minimal sets of conditional attributes
National Category
Mathematics
Identifiers
URN: urn:nbn:se:bth-8889Local ID: oai:bth.se:forskinfoD40F71B7BE21B3A6C12573640062A139ISBN: 978-83-60282-03-8 (print)OAI: oai:DiVA.org:bth-8889DiVA: diva2:836660
Conference
Computers in Medical Activity
Available from: 2012-09-18 Created: 2007-09-28 Last updated: 2016-09-20Bibliographically approved

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Rakus-Andersson, Elisabeth
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