Abstract—This paper applies the association rules method to discover the relationship between metabolic syndrome and its chronic diseases. The sample data used in this research is medical records specified to metabolic syndrome patients in a large government hospital. The Apriori and FP-Growth algorithms are chosen to be compared in the performance and applicable results of extracting the relationship of the metabolic syndrome patient records represented by ICD-10 code. The results show that the Apriori can extract 6 rules and 724 rules from FP-Growth. The comparative results between Apriori and FP-Growth found that 6 rules are common. The overall results show that the metabolic syndrome patients mostly have strong relationships with hypertension, obesity and diabetes. Interestingly, these diseases often occur with the patients was diagnosed that was metabolic syndrome. Additionally, the results would bring to the suggestion in metabolic syndrome patients to know about the relationship of these chronic diseases. Moreover, the physicians could use this guide for the treatment strategy in the future.
Index Terms—association rules, Apriori, FP-Growth, metabolic syndrome, chronic diseases, ICD-10
Cite: Supak Iamongkot, Sotarat Thammaboosadee, and Supaporn Kiattisin, "Discovering Association between Metabolic Syndrome and its Related Chronic Diseases Represented by ICD-10 Code," Vol. 6, No. 4, pp. 258-261, November, 2015. doi: 10.12720/jait.6.4.258-261
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