Application of CBR in Developing a Prototype Swine Flu Medical Recommender

Case Based Reasoning (CBR) has become a successful methodology for problem solving, reasoning and learning. It is applied for diagnosis and decision support in the medical field in several areas. This is because CBR methodology is analogous to the process of human reasoning and natural problem solving. In this paper, a Swine Flu Medical Recommender (SFMR) prototype is applied using CBR that assists in diagnosis of Swine Flu. Knowledge is represented as cases of Swine Flu and stored in case base (CB). The system receives a problem case as a Query, compares it with previous cases for similarity in the CB using an algorithm for Similarity, and returns a fixed set of most similar cases that may be directly used to solve the problem or may be adapted with modifications within the restrictions of the Query.