John Yearwood

AWSum - applying data mining in a health care scenario

This paper investigates the application of a new data mining algorithm called Automated Weighted Sum, (AWSum), to diabetes screening data to explore its use in providing researchers with new insight into the disease and secondarily to explore the potential the algorithm has for the generation of prognostic models for clinical use. There are many data mining classifiers that produce high levels of predictive accuracy but their application to health research and clinical applications is limited because they are complex, produce results that are difficult to interpret and are difficult to integrate with current knowledge and practises. This is because most focus on accuracy at the expense of informing the user as to the influences that lead to their classification results. By providing this information on influences a researcher can be pointed to new potentially interesting avenues for investigation. AWSum measures influence by calculating a weight for each feature value that represents its influence on a class value relative to other class values. The results produced, although on limited data, indicated the approach has potential uses for research and has some characteristics that may be useful in the future development of prognostic models.

Collective Reasoning and Coalescing Reasoning

In this chapter, we consider in some detail the nature of collective reasoning and the existing approaches to supporting the collective reasoning that reasoning communities undertake. In approaching the development of technologies to support the functioning of reasoning communities, it is important to be clear on the nature of the tasks involved in collective reasoning. In Chapter 1, we have outlined the main tasks of collective reasoning as: individual reasoning, reasoning communication, and the coalescing of reasoning. However, it is important to identify the ways in which collective reasoning is indeed cognitive cooperation and to what extent there is a case that it is mutually beneficial cooperation as well as being beneficial in its outcomes. DOI: 10.4018/978-1-4666-1818-3.ch002