CASE-BASED REASONING FOR AIDS INITIAL ASSESSMENT

Case-based reasoning solves a problem by retrieving from its case memory a solution which has solved a similar problem in the past, and then adapting the solution to the problem. Recent work in knowledge-based systems in AIDS initial assessment (AIA) reflects a growing interest in the case-based paradigm. The reason is that AIA experts rely heavily on memory of previous cases when assessing AIDS-risky behaviors. The paper describes a case-based system that uses experience in the form of previous cases to assess AIDS-risky behaviors. An important feature of the system is that fuzzy mathematical algorithms are used to retrieve previous cases and determine the best matching case. The paper concludes with a discussion of future research.