Analysis of health care data using different data mining techniques

Abstract

Data mining is an interesting field of research whose major objective is to acquire knowledge from large amounts of data. With advances in health care related research, there is a wealth of data available. However, there is a lack of effective analytical tools to discover hidden and meaningful patterns and trends in data, which is essential for any research. In recent years, human immune-deficiency virus (HIV) related illnesses have become a threat to the modern world. Researchers all over world, including India, are trying hard to find suitable answer to this and this led to lots of research in the field. Therefore, a tool which can process data in meaningful way is the need the time. In this study, we briefly examine the potential use of classification based data mining techniques such as decision tree and association rule to massive volume of health care data. Further we developed a prototype/approach that is specially designed to monitor the patients receiving antiretroviral therapy (ART). As monitoring of individual is not a difficult task however deriving inferences from a large cohort and then use this information for future guidelines need this kind of prototype/approach. We expect, this would have great impact in current management and future strategies against HIV.