Communications - Scientific Letters of the University of Zilina 2013, 15(1):68-73 | DOI: 10.26552/com.C.2013.1.68-73

Hepatitis B Disease Diagnosis Using Rough Set

Tomasz Kanik1
1 Department of Mathematical Methods, Faculty of Management Science and Informatics, University of Zilina, Slovakia

This paper describes processing of the medical data by means of the prediction system based on Rough Set Theory (RST). The Rough Sets proved to be very useful for the analysis of the decision problems concerning objects described in a data table by a set of condition attributes as well as a set of decision attributes. In order to make efficient data analysis and suggestive predictions in a case of the data of patients suffering from viral hepatitis were used to predict a probability of their death or serious disability. This paper also demonstrates an extension of the Rough Set methodology for reducing number of input data in order to increase prediction accuracy without loss of knowledge.

Keywords: Index Terms - Rough Set, hepatitis, machine learning, prediction system

Published: March 31, 2013  Show citation

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Kanik, T. (2013). Hepatitis B Disease Diagnosis Using Rough Set. Communications - Scientific Letters of the University of Zilina, 15(1), 68-73. doi: 10.26552/com.C.2013.1.68-73
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