A research submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information Management, School of Engineering and Technology

Research studies project report (M. Eng.) - Asian Institute of Technology, 2017

Data mining is about extracting useful information from huge databases. These days to overcome the problem of massive data management most of the organizations have shifted their traditional way of recording data to electronic based systems. Data mining techniques are being used by various organizations to have better outcomes or predictions. Healthcare is one of the industries using data mining techniques. In this paper, data mining techniques are used to predict risk level of having heart diseases of a patient. These days there are lots of deaths due to heart attacks and heart diseases. Patients go through too many tests to know the actual disease to get treated. This process of too many tests either costs them lot of money or sometimes lives too. To overcome this problem, a system is developed which can predict heart diseases in a patient looking at the basic attributes like age, gender, blood pressure, cholesterol level and few more. The main objective of the research is to create a system which predicts risk levels of heart diseases and apply KNN and ID3 data mining techniques to know the better technique for accurate results. The results show that KNN algorithm gives better performance than ID3 algorithm. This system is helpful to have quick solutions to know the likelihood of having heart diseases of a patient.