Fashions in Data Mining and Hidden Knowledge Innovation from Clinical Database

Abstract

Data Mining and Hidden Knowledge Innovation (DMHKI) is one of the fast growing computer science fields. Its reputation is caused by an increased demand for tools that help with the analysis and understanding of huge amounts of data in Clinical Database. Such data are generated on a daily basis by Hospitals. This explosion came into being through the ever increasing use of computers, scanners, digital cameras, bar codes, etc. We are in a situation when rich sources of data, stored in databases, warehouses, and other data repositories, are readily available. This in turn causes big interest of medicalsocieties in the field of DMHKI. What is needed is a clear and simple methodology for extracting the knowledge that is hidden in the database. In this chapter, an integrated DMHKI process model based on the emerging technologies like XML, PMML, SOAP, UDDI, and OLE BD-DM is introduced. These technologies help designing flexible, semi-automated, and easy to use DMHKI model. They enable the building of knowledge repositories. They allow for communication between several data mining tools, databases and knowledge repositories. They also enable integration and automation of DMHKI tasks. The Journal describes a Seven-step DMHKI process model, the above mentioned technologies, and their implementation details.

Keywords

Data Mining, Hidden Knowledge Innovation, Clinical Database

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