Turning medical data into decision-support knowledge

Advances in information collection and analysis are reaching the point of providing physicians with the help of computer-based assistants. These systems will provide rapid second opinions to physicians in a clinical setting as well as assist them in the analysis of large sets of patient descriptions for research purposes. This paper presents INC2.5 as such a decision-support system. INC2.5 extracts information from databases of previously seen patients to build a decision tree which is used to predict the outcome of new patients on a chosen variable. The concept of matching new patients with the most similar previously seen patient, on which INC2.5 is based, can be easily understood by its users. Further adding to INC2.5's ease of use is its flexibility in allowing users to customize decision trees to their liking. In order to convey the uncertainty of the environment, INC2.5 presents all decisions with a confidence factor.