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A knowledge discovery from incomplete coronary artery disease datasets using rough set

Incompleteness of datasets is one of the important issues in the area of knowledge discovery in medicine. This study proposes a rough set theory (RST)-based knowledge discovery from coronary artery disease (CAD) datasets when there are only small number of objects and contain missing data (incomplet...

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Main Author: Ahmad Fadzil, Mohd Hani
Format: Article
Published: Inderscience Enterprises 2011
Subjects:
RB Pathology
QA75 Electronic computers. Computer science
Online Access:http://www.inderscience.com/
http://eprints.utp.edu.my/6693/
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spelling my.utp.eprints.66932014-03-31T17:36:25Z A knowledge discovery from incomplete coronary artery disease datasets using rough set Ahmad Fadzil, Mohd Hani RB Pathology QA75 Electronic computers. Computer science Incompleteness of datasets is one of the important issues in the area of knowledge discovery in medicine. This study proposes a rough set theory (RST)-based knowledge discovery from coronary artery disease (CAD) datasets when there are only small number of objects and contain missing data (incomplete). At first, RST combined with artificial neural network (ANN) is developed to impute the missing data of the datasets. Then, the knowledge that is discovered from imputed datasets is used to evaluate the quality of the imputation. After that, RST is applied to extract rules from the imputed datasets. This will result in a large number of rules. Rule selection based on the quality of extracted rules is investigated. All the evaluation and selection are based on the complete datasets. Finally, the selected small number of rules is evaluated. The discovered selected rules are used as a classifier on the diagnosis of the presence of CAD to demonstrate their good performance. Inderscience Enterprises 2011-03 Article PeerReviewed http://www.inderscience.com/ Ahmad Fadzil, Mohd Hani (2011) A knowledge discovery from incomplete coronary artery disease datasets using rough set. International Journal of Medical Engineering and Informatics, Volume 3, Issue 1, March 2011, Pages 60-77 (1). pp. 60-77. ISSN 17550653 http://eprints.utp.edu.my/6693/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic RB Pathology
QA75 Electronic computers. Computer science
spellingShingle RB Pathology
QA75 Electronic computers. Computer science
Ahmad Fadzil, Mohd Hani
A knowledge discovery from incomplete coronary artery disease datasets using rough set
description Incompleteness of datasets is one of the important issues in the area of knowledge discovery in medicine. This study proposes a rough set theory (RST)-based knowledge discovery from coronary artery disease (CAD) datasets when there are only small number of objects and contain missing data (incomplete). At first, RST combined with artificial neural network (ANN) is developed to impute the missing data of the datasets. Then, the knowledge that is discovered from imputed datasets is used to evaluate the quality of the imputation. After that, RST is applied to extract rules from the imputed datasets. This will result in a large number of rules. Rule selection based on the quality of extracted rules is investigated. All the evaluation and selection are based on the complete datasets. Finally, the selected small number of rules is evaluated. The discovered selected rules are used as a classifier on the diagnosis of the presence of CAD to demonstrate their good performance.
format Article
author Ahmad Fadzil, Mohd Hani
author_facet Ahmad Fadzil, Mohd Hani
author_sort Ahmad Fadzil, Mohd Hani
title A knowledge discovery from incomplete coronary artery disease datasets using rough set
title_short A knowledge discovery from incomplete coronary artery disease datasets using rough set
title_full A knowledge discovery from incomplete coronary artery disease datasets using rough set
title_fullStr A knowledge discovery from incomplete coronary artery disease datasets using rough set
title_full_unstemmed A knowledge discovery from incomplete coronary artery disease datasets using rough set
title_sort knowledge discovery from incomplete coronary artery disease datasets using rough set
publisher Inderscience Enterprises
publishDate 2011
url http://www.inderscience.com/
http://eprints.utp.edu.my/6693/
_version_ 1738655512833032192
score 13.211869

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