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Rough set theory in the classification of diagnoses
Ansvarlig organisasjon
2009 (engelsk)Konferansepaper, Publicerat paper (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
Berlin: Springer , 2009.
Emneord [en]
fuzzy sets, rough set theory, medical diagnosis
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-8984ISI: 000273952000005Lokal ID: oai:bth.se:forskinfo4BD52A91D726B9D6C125733E004CEF2BISBN: 978-3-642-04461-8 (tryckt)OAI: oai:DiVA.org:bth-8984DiVA, id: diva2:836760
Konferanse
International Conference on Computers in Medical Activity 2007
Merknad
Conference Information: International Conference on Computers in Medical Activity Lodz, POLAND, 2007 Coll Comp Sci; Polish Soc Med Comp Sci Source: COMPUTERS IN MEDICAL ACTIVITY Book Series: Advances in Intelligent and Soft Computing Volume: 65 Pages: 41-51 Published: 2009Tilgjengelig fra: 2012-09-18 Laget: 2007-08-21 Sist oppdatert: 2016-09-20bibliografisk kontrollert

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Rakus-Andersson, Elisabeth

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Totalt: 44 treff
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