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Efficient Implementation of FP Growth Algorithm-Data Mining on Medical Data


Abdullah Saad Almalaise Alghamdi


Vol. 11  No. 12  pp. 7-16


Data mining plays an essential role for extracting knowledge from large databases from enterprises operational databases. Everyday organizations collect huge amount of data from several resource. Whereas medical data is consider most famous application to mine that data to provide interesting patterns or rules for the future perspective. Data mining implementation on medical data to generate rules and patterns using Frequent Pattern (FP)-Growth algorithm is the major concern of this research study. We presented in this paper how data mining can apply on medical data. Therefore, empirical data and result presented in this paper to provide more guidance to the doctors as well as more understanding about the relation of a doctor and a patient. For this, we first discussed about the importance of data mining using medical data then discussion of general data mining techniques has been presented. Furthermore, methodology describes the conceptual model for the extraction of rules on medical databases finally result can guide the relationship between the different attributes presented in the data.


Medical Data Mining, Association Mining, FP-Growth Algorithm