Chiang Mai Journal of Science

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 The study focuses on mining association rules from asthma patients profile dataset. The mining framework involves two main phases that are data preparation phase and association rules mining phase. The data preparation phase consumes much effort due to the large amount of data obtained. Statistical approaches are used to ensure the dataset is appropriately distributed for mining process. The association rules mining phase uses an algorithm known as Apriori Algorithm. Association rules mining is a data mining task that finds relationships among attributes in large datasets The discovered rules may help discover new information, market analysis and support decision making. The experimental result produces factors or item sets influencing asthma patients in the form of association rules. It discovers interesting and strong relationship among attributes in the asthma profile patient dataset which could provide new medical discovery as well as strengthening the existing knowledge about the illness. As a result, this study gave great advantage to medical practitioners concerning asthma disease.

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