A multiple approach to data analysis and uncertainty management in knowledge-based systems

This paper compares three different data analysis methods in a subfield of the coronary heart disease risk assessment (CHDRA) area-the identification of increased blood cholesterol levels. A data set containing the cholestero l data of 166 persons is employed as a test case, and analyzed in three exp erimental investigations. The first analysis method employs a predominantly knowledge-based fuzzy expert system solution to the problem. The second me thod employs statistical discriminant analysis on the same data, whereas th e results of the third analysis are obtained by an artificial neural networ k. This study evaluates the advantages as well as the disadvantages of each method. Special attention is given to the systems' individual capability f or managing the uncertainty involved in the decision-making process. The re sults achieved in the study provide evidence for the complementary and mutu ally supporting character of the different approaches. (C) 2000 John Wiley & Sons, Inc.