ABSTRACT

This chapter summarizes the research work conducted and its significant outcomes. Also, it points to the future work and its implications. A framework (Intelligent Optimization Unit) for clinical data analysis has been proposed which can be explicitly used for evaluating and predicting the risk related to a specific disease with any of the combination of algorithms. Nature-inspired computing plays a significant role in disease prediction and classification with medical informatics. Risk factor analysis in medical is a vital problem in recent days. The determination of risk factors with regard to location, likelihood, and dietary habits is the one that is essentially needed by medical experts. The research work presents a decision support model using feature selection and data classification with statistical significance. A unified Intelligent Optimization Unit has been developed which suits all possible combinations of feature selection and data classification techniques.