A Unified Approach for Discovery of Interesting Association Rules in Medical Databases

Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining - Lecture Notes in Computer Science ◽

10.1007/11790853_5 ◽

2006 ◽

pp. 53-63 ◽

Cited By ~ 7

Author(s):

Harleen Kaur ◽

Siri Krishan Wasan ◽

Ahmed Sultan Al-Hegami ◽

Vasudha Bhatnagar

Keyword(s):

Association Rules ◽

Unified Approach ◽

Medical Databases

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An Efficient Interestingness based Algorithm for Mining Association Rules in Medical Databases

Advances and Innovations in Systems, Computing Sciences and Software Engineering ◽

10.1007/978-1-4020-6264-3_30 ◽

2007 ◽

pp. 167-172 ◽

Cited By ~ 1

Author(s):

Siri Krishan Wasan ◽

Vasudha Bhatnagar ◽

Harleen Kaur

Keyword(s):

Association Rules ◽

Medical Databases ◽

Mining Association Rules

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Mining Medical Databases Using Graph based Association Rules

International Journal of Machine Learning and Computing ◽

10.7763/ijmlc.2013.v3.324 ◽

2013 ◽

pp. 294-296 ◽

Cited By ~ 1

Author(s):

Wael Ahmad AlZoubi

Keyword(s):

Association Rules ◽

Medical Databases

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Mining Medical Databases Using Proposed Incremental Association Rules Algorithm (PIA)

Second International Conference on the Digital Society ◽

10.1109/icds.2008.10 ◽

2008 ◽

Cited By ~ 1

Author(s):

Laila Elfangary ◽

Walid Adly Atteya

Keyword(s):

Association Rules ◽

Medical Databases

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Mining association rules with improved semantics in medical databases

Artificial Intelligence in Medicine ◽

10.1016/s0933-3657(00)00092-0 ◽

2001 ◽

Vol 21 (1-3) ◽

pp. 241-245 ◽

Cited By ~ 48

Author(s):

Miguel Delgado ◽

Daniel Sánchez ◽

Marı́a J Martı́n-Bautista ◽

Marı́a-Amparo Vila

Keyword(s):

Association Rules ◽

Medical Databases ◽

Mining Association Rules

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DETECTING CRITICAL LEAST ASSOCIATION RULES IN MEDICAL DATABASES

International Journal of Modern Physics Conference Series ◽

10.1142/s2010194512005557 ◽

2012 ◽

Vol 09 ◽

pp. 464-479 ◽

Cited By ~ 4

Author(s):

ZAILANI ABDULLAH ◽

TUTUT HERAWAN ◽

MUSTAFA MAT DERIS

Keyword(s):

Breast Cancer ◽

Association Rules ◽

Mathematical Formulation ◽

Medical Data ◽

Emission Computed Tomography ◽

Proton Emission ◽

Database Mining ◽

Scalable Algorithm ◽

Medical Databases ◽

Medical Dataset

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.

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