Association Rule Mining for Multifactorial Diseases: Survey and Opportunities

Association Rule Mining is an efficient Data Mining task that has been largely used in health informatics research since its emergence. As health informatics and in particular multifactorial diseases have received a lot of attention from researchers in the last decade, and have shown its great importance, it is therefore worth considering the state of the art of multifactorial diseases research. Since researchers and knowledge discovery experts have implemented a set of Data Mining techniques for knowledge extraction from health data, the application of Association Rule Mining techniques for multifactorial diseases has been condensed and investigated in detail in this study. The limitations related to the applications of Association Rule Mining for the discovery of factors responsible for multifactorial diseases were highlighted and recommendations were gived to address these limitations. In addition, algorithms and tools employed for the application of Association Rule Mining were also specified, conclusions were learned from the reviewed literature, and future research guidelines were provided.