Disease pattern discover in institutional data via cluster analysis

In this presents study to discover the disease patterns by using statistical approach on institutional database. This study, help to know about the number of patients attended in OPD with different ailments for every year. By the help of data mining technique, the study is designed to discover the patterns and hidden relationships in dataset. Actually data mining technique is used to extract information from a data set and transform it into an understandable structure for further uses. The main aims of this study to provide profiling of patients, discover dominant disease and dominant month via cluster analysis. A cluster is a collection of data objects which are similar to one another within the same cluster and are dissimilar to the objects in other clusters. In this regard, clustering is used to profile patients according to their month of GOPD in the institute. The gap statistic used to find the optimum numbers of clusters in dataset. Using this, a number of clusters are formed on the basis of type of disease acquired by patients, demographic and socioeconomic characteristics beside that patients are grouped into different clusters according to their disease.