Automatic detection of heart disease using an artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism and k-nn (nearest neighbour) based weighting preprocessing
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Date
2007
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
It is evident that usage of machine learning methods in disease diagnosis has been increasing gradually. In this study, diagnosis of heart disease, which is a very common and important disease, was conducted with such a machine learning system. In this system, a new weighting scheme based on k-nearest neighbour (k-nn) method was utilized as a preprocessing step before the main classifier. Artificial immune recognition system (AIRS) with fuzzy resource allocation mechanism was our used classifier. We took the dataset used in our study from the UCI Machine Learning Database. The obtained classification accuracy of our system was 87% and it was very promising with regard to the other classification applications in the literature for this problem. (C) 2006 Elsevier Ltd. All rights reserved.
Description
Keywords
heart disease, artificial immune system, AIRS, k-nn based weighting preprocessing, expert systems
Journal or Series
EXPERT SYSTEMS WITH APPLICATIONS
WoS Q Value
Q1
Scopus Q Value
Q1
Volume
32
Issue
2
