Modified K-Means Clustering Algorithm for Disease Prediction

Data Mining is known as the process of extraction of knowledge or useful patterns from the unorganized and huge data. The goal of data mining is to analyze different type of data by using available data mining tools. The steps in data mining are: Data cleaning, Data Integration, data selection, data transformation, data mining, pattern evaluation and knowledge representation. Data mining plays an important role in medical for prediction of disease. There are high risky consequences because of doctor’s assumptions and lack of knowledge in particular area. Data mining here plays an important role in discovering or deriving out useful patterns from the historic data of patients, from these patterns prediction analysis for future aspects can be done [1]. Data Mining is the process of analyzing the huge amount of data and encapsulating the relevant information from it. In other words, we can say that data mining is the procedure of mining knowledge from data. The information extracted can be used for any of the following fields of application –