Towards Role Based Hypothesis Evaluation for Health Data Mining

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

Establishing a lineage for medical knowledge discovery

Medical science has a long history characterised by incidents of extraordinary insights that have resulted in a paradigm shift in the methodologies and approaches used and have moved the discipline forward. While knowledge discovery has much to offer medicine, it cannot be done in ignorance of either this history or the norms of modern medical investigation. This paper explores the lineage of medical knowledge acquisition and discusses the adverse perceptions that data mining techniques will have to surmount to gain acceptance.Sydney, NS

On the arguments against the application of data mining to medical data analysis

There is a variety of criticisms of medical data mining which has led, in some cases, to the technology being overlooked as a tool. This paper presents a discussion of six of the strongest arguments against the application of data mining to the complex field of human medicine. The aim of the paper is to raise the predominant issues and suggest solutions whilst also opening the issues for further consideration by both medical and information technology communities