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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| Format: | Article |
| Language: | English |
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World Scientific Publishing
2010
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| 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 |
| _version_ | 1848816975965323264 |
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| author | Herawan, Tutut |
| author_facet | Herawan, Tutut |
| author_sort | Herawan, Tutut |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T01:14:25Z |
| format | Article |
| id | ump-2066 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T01:14:25Z |
| publishDate | 2010 |
| publisher | World Scientific Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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. (Published) |
| spellingShingle | T Technology (General) R Medicine (General) Herawan, Tutut Detecting Critical Least Association Rules In Medical Databases |
| title | Detecting Critical Least Association Rules In Medical Databases
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| title_full | Detecting Critical Least Association Rules In Medical Databases
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| title_fullStr | Detecting Critical Least Association Rules In Medical Databases
|
| title_full_unstemmed | Detecting Critical Least Association Rules In Medical Databases
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| title_short | Detecting Critical Least Association Rules In Medical Databases
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| title_sort | detecting critical least association rules in medical databases |
| topic | T Technology (General) R Medicine (General) |
| 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 |