Rough set theory in the classification of diagnoses

Document type: Conference Papers
Peer reviewed: Yes
Author(s): Elisabeth Rakus-Andersson
Title: Rough set theory in the classification of diagnoses
Conference name: International Conference on Computers in Medical Activity 2007
Year: 2009
Pagination: 41-51
ISBN: 978-3-642-04461-8
Publisher: Springer
City: Berlin
ISI number: 000273952000005
Organization: Blekinge Institute of Technology
Department: School of Engineering - Dept. Mathematics and Science (Sektionen för teknik – avd. för matematik och naturvetenskap)
School of Engineering S- 371 79 Karlskrona
+46 455 38 50 00
Authors e-mail:
Language: English
Abstract: 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.
Subject: Mathematics\General
Mathematics\Discrete Mathematics
Keywords: fuzzy sets, rough set theory, medical diagnosis
Note: 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: 2009