Analysis of HCV Risk Factor among PWID’s in India- An Approach using Naive Bayes Classifier

Abstract: The huge amount of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods as the way in which healthcare is financed is critical for equity in access to healthcare. At present the proportion of public resources committed to healthcare in India is one of the lowest in the world, with less than one-fifth of health expenditure being publicly financed. To overcome this issue the researchers, use data mining techniques. Data mining through various algorithms provides the methodology and technology to transform large amount of data into useful information for decision making and patients receive better, more affordable healthcare services. In this paper, Naive Bayes algorithm is used to predict the risk factors associated with HCV infection among People Who Inject Drugs (PWID�s) in India. Naive Bayes algorithm are the most popular algorithms for rule based classification as it requires minimal number of attributes.

Keywords: Data Mining, Naive Bayes Algorithm, PWID, HCV.