Paper Details: Downloads: 499
Serial Number: P1120429001
Title: MINING PATIENT DATA BASED ON ROUGH SET THEORY TO DETERMINE THROMBOSIS DISEASE
Authors: Abdel Badeeh M. Salem and Mohamed Roushdy and Safia A.Mahmoud
Abstract: This paper applies the knowledge discovery process over medical data set using the rough set theory as a data mining technique. The aim is to apply rough set concepts and the reduction algorithm to search for patterns specific/sensitive to thrombosis disease. The mining efforts show that the developed reduction algorithm minimizes the set of original attributes from 60 to 16 significant attributes Filtering the discovered knowledge we obtains 14 patterns which can help to predict thrombosis disease. The discovered rules have been successfully evaluated by expert physicians in this domain.
Keywords: Rough Sets, Data mining, Knowledge Discovery in Database (KDD), Medical Informatics
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume: 5
Issue: 1
Submission Date: 8/1/2004 12:00:00 AM
Review Date: 12/1/2004 12:00:00 AM
Publishing Date: 3/1/2005 12:00:00 AM
Article Downloads: 499
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