Abstract
Association Rule Discovery is a significant data mining technique. In this paper, we applied this technique to discover fundamental association among a data set of diabetes mellitus (DM) patients with ophthalmic complication using a classifier based on gender, age and payment method of treatment expense. The result indicated that “diabetes mellitus (DM) patients Type II aging between 60-69 years old with no occupation whose payment for their treatment expense was by Government Official Rights of Continuous Treatment tended to have diabetes mellitus (DM) with ophthalmic complication.” This conclusion is useful for healthcare treatment of adulthood patients, welfare improvement of public healthcare, provision of helpful recommendation for diabetes mellitus patients and further development in finding disease complication.
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Kasemthaweesab, P., Kurutach, W. (2011). Study of Diabetes Mellitus (DM) with Ophthalmic Complication Using Association Rules of Data Mining Technique. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_52
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DOI: https://doi.org/10.1007/978-3-642-23935-9_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23934-2
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