DATA MINING FOR HUMAN HEALTH AND WELL BEING

Abstract

Health-care industry today generates large amount of complex data about patients, hospitals resources, disease diagnosis, electronic patient records, medical devices etc.The large amounts of data is a key resource to be processed and analyzed for knowledge extraction that enables support for cost-savings and decision making. Some vast data sources like census tracts has lots of raw data from which many interesting pattern and associative rules can be found.Census data provides raw facts about a particular location.These Geo spatial data can be used to predict or find interesting pattern location wise.Region wise pattern recognition helps us to design region specific solution for a particular problem that could save lot of time and resource since the focus is on the particular location for a particular problem.Also interesting Association rules can be find out among these attributes which gives us insight of relationship among these attributes. In this report we have analyzed accuracy results of various datamining prediction model on these type of data.Also we had applies Apriori algorithm to mine Association rules on it.We had used chronic disease data on which various prediction models are to be build and the relationship between Unhealthy Behavior,Health Outcomes and Prevention measures is to be found out