A Novel Approach for Analysis of Breast Cancer and Mental Health Using Various Data Mining Tools

Abstract: Data mining is a relatively new field of research whose major objective is to acquire knowledge from large amounts of data. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available. But the large amount of data cannot be processes by human being in the limited period. So we are using various data mining tools to process these data in health care efficiently and in the timely manner. We can also have expected outcome rather than manual calculation. In this dissertation we consider two types of medical database which one shows the analysis of breast cancer using various data mining and another one for mental health as a case study. Here the breast cancer consists of 10 attributes whereas minimum data set for mental health having 455 attributes. In this dissertation we consider some of the tools such as weka, cruise, discover E to evaluate and to develop classification rule rather than using some data mining algorithms. We can have most probably 70% to 80% accurate result. A further extension of the dissertation is to store this data into PDA and storing some of the classification rule to classify the amount of data which are available to provide real time assistance to reactionaries.