Distributed Storage and Integrity Auditing Mechanism for Secure Cloud Storage

Abstract: Data mining is a phenomenon which analyzes large volumes of data and extracts patterns that can be converted to useful knowledge. The data mining techniques can be applied on medical data which has abundant scope to improve Quality of Service in Healthcare industry. Electronic health records and other historical medical data available in textual and graphical formats are a gold mine to researchers in the field. Medical data mining techniques analyze latent medical attributes and the relationships among them to bring about expert decisions in curing diseases. Data mining techniques can also be used toknow the frequently occurring diseases in the local databases. In this paper we present a methodology to discover locally frequent diseases with the help of Apriori data mining technique. We also used visualization techniques to present the trends graphically. We built a prototype application that demonstrates the efficiency of the method. The empirical results revealed that the prototype is useful and can be used in real world Healthcare tools.

Keywords: Data mining techniques, frequent item sets, medical data mining, locally frequent patterns, Apriori