Discovering Sequential Patterns from Medical Datasets

Sequential patterns mining from data is a well stated data mining problem. It has a number of applications such as DNA sequencing, signal processing, speech analysis etc. In this problem, it is require to mine the causal relationship between different events. An event is a non-empty disordered collection of items. One of the important applications of sequential pattern mining is in medical data. Sequential mining from medical data is actually finding causal relationship between different diseases or symptoms available on the patients of any geographical location. Medical data contains all the information about the diseases of the patients. It is ordered according to the time of visit of the patients in the hospital. Such data may provide the valuable information about the cause and effect one disease on another. In this paper, we propose a method of extracting sequential patterns from such medical data. The efficacy of our method is established by the experiment conducted with a dataset collected from a Private Hospital of Albaha, Kingdom of Saudi Arabia.