A novel extracting medical diagnosis rules based on rough sets

Abstract

Analysis of how to extract medical diagnosis rules from medical cases. Based on the rough set theory, a way of acquiring knowledge is introduced. Using this theory, we analyze the data, propose some possible rules and reveal an optimized probability formula. The steps of implementation, which includes the continual information discrimination system, information reduction system, decision acquirement rules, decision model generation, etc., are explained through case study. In the end, the whole process of knowledge acquirement is discussed, which can effectively solve the choke point problem of acquiring knowledge in the expert system. At the same time, it also provides a new way to solve the application of artificial intelligence technology in the field of medicinal diagnosis.