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. T hese systems will provide rapid second opinions to physicians in a cli nical 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 d atabases 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 see n patient, on which INC2.5 is based, can be easily understood by its u sers. Further adding to INC2.5's ease of use is its flexibility in all owing users to customize decisions trees to their liking. In order to convey the uncertainty of the environment, INC2.5 presents all decisio ns with a confidence factor.