Detecting Critical Least Association Rules In Medical Databases

Least association rules are corresponded to the rarity or irregularity relationship among itemset in database. Mining these rules is very difficult and rarely focused since it always involves with infrequent and exceptional cases. In certain medical data, detecting these rules is very critical and m...

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Main Author:	Herawan, Tutut
Format:	Article
Language:	English
Published:	World Scientific Publishing 2010
Subjects:	T Technology (General) R Medicine (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/2066/ http://umpir.ump.edu.my/id/eprint/2066/1/Full_Paper_ICMCB_MB_28_Detecting_Critical_Least_Association_Rules_In_Medical_Databasess-Journal-.pdf

id	ump-2066
recordtype	eprints
spelling	ump-20662017-09-14T05:37:18Z http://umpir.ump.edu.my/id/eprint/2066/ Detecting Critical Least Association Rules In Medical Databases Herawan, Tutut T Technology (General) R Medicine (General) Least association rules are corresponded to the rarity or irregularity relationship among itemset in database. Mining these rules is very difficult and rarely focused since it always involves with infrequent and exceptional cases. In certain medical data, detecting these rules is very critical and most valuable. However, mathematical formulation and evaluation of the new proposed measurement are not really impressive. Therefore, in this paper we applied our novel measurement called Critical Relative Support (CRS) to mine the critical least association rules from medical dataset. We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. Experiment with two benchmarked medical datasets, Breast Cancer and Cardiac Single Proton Emission Computed Tomography (SPECT) Images proves that CRS can be used to detect to the pertinent rules and thus verify its scalability. World Scientific Publishing 2010 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/2066/1/Full_Paper_ICMCB_MB_28_Detecting_Critical_Least_Association_Rules_In_Medical_Databasess-Journal-.pdf Herawan, Tutut (2010) Detecting Critical Least Association Rules In Medical Databases. International Journal of Modern Physics: Conference Series, 1 (1). pp. 1-5. ISSN 2010-1945
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	T Technology (General) R Medicine (General)
spellingShingle	T Technology (General) R Medicine (General) Herawan, Tutut Detecting Critical Least Association Rules In Medical Databases
description	Least association rules are corresponded to the rarity or irregularity relationship among itemset in database. Mining these rules is very difficult and rarely focused since it always involves with infrequent and exceptional cases. In certain medical data, detecting these rules is very critical and most valuable. However, mathematical formulation and evaluation of the new proposed measurement are not really impressive. Therefore, in this paper we applied our novel measurement called Critical Relative Support (CRS) to mine the critical least association rules from medical dataset. We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. Experiment with two benchmarked medical datasets, Breast Cancer and Cardiac Single Proton Emission Computed Tomography (SPECT) Images proves that CRS can be used to detect to the pertinent rules and thus verify its scalability.
format	Article
author	Herawan, Tutut
author_facet	Herawan, Tutut
author_sort	Herawan, Tutut
title	Detecting Critical Least Association Rules In Medical Databases
title_short	Detecting Critical Least Association Rules In Medical Databases
title_full	Detecting Critical Least Association Rules In Medical Databases
title_fullStr	Detecting Critical Least Association Rules In Medical Databases
title_full_unstemmed	Detecting Critical Least Association Rules In Medical Databases
title_sort	detecting critical least association rules in medical databases
publisher	World Scientific Publishing
publishDate	2010
url	http://umpir.ump.edu.my/id/eprint/2066/ http://umpir.ump.edu.my/id/eprint/2066/1/Full_Paper_ICMCB_MB_28_Detecting_Critical_Least_Association_Rules_In_Medical_Databasess-Journal-.pdf
first_indexed	2023-09-18T21:55:35Z
last_indexed	2023-09-18T21:55:35Z
_version_	1777414056272986112

Detecting Critical Least Association Rules In Medical Databases

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