Analyzing patterns of numerously occurring heart diseases using association rule mining

Abstract

The use of technology and science in Healthcare has made services available to all the people along with ensuring the best care for the people. Data Mining provides us such useful techniques, which can help the medical practitioners to effectively analyze and discover large amount of data in a more efficient and convenient way as now electronic recording system of data has come into existence. Therefore, millions of data are now available and majority of them would have been remained undiscovered, if the data mining techniques were not introduced. In our work, an association based rule mining technique has been used to identify such hidden patterns of the most commonly occurring heart diseases namely Unstable Angina(UA), Myocardial Infarction(MI), Coronary Heart Disease(CHD) etc. among Bangladeshi people and unravelling the hidden information by analyzing the results. Basically, other researchers in this field used the classification and clustering methods of data mining by which they could predict the chance of occurring heart diseases and clustered them to identify the dependency of one attribute to another. The trends or patterns for heart diseases may vary depending on sex, age, socioeconomic condition, demographic regions and so on. The objective of our work is to find out those hidden trends or patterns. Therefore, we have chosen association rule mining technique to find those patterns or trends among patients depending on their age, sex, regions and socioeconomic condition.