Towards Role Based Hypothesis Evaluation for Health Data Mining
Anna Shillabeer, John F Roddick
Data mining researchers have long been concerned with the application of tools to facilitate and improve data analysis on large, complex data sets. The current challenge is to make data mining and knowledge discovery systems applicable to a wider range of domains, among them health. Early work was performed over transactional, retail based data sets, but the attraction of finding previously unknown knowledge from the ever increasing amounts of data collected from the health domain is an emerging area of interest and specialisation. The problem is finding a solution that is suitably flexible to allow for generalised application whilst being specific enough to provide functionality that caters for the nuances of each role within the domain. The need for a more granular approach to problem solving in other areas of information technology has resulted in the use of role based solutions. This paper discusses the progress to date in developing a role oriented solution to the problem of providing for the diverse requirements of health domain data miners and defining the foundation for determining what constitutes an interesting discovery in an area as complex as health.
Data Mining; Data Analysis; Electronic Health Records; Role-based; Medicine