Frameworks for u Health Care System Using Fuzzy Functions
Haeng-Kon Kim · 2010
Abstract — In this paper, we show an intelligent disease diagnosis system for public. Our system deals with 30 diseases and their typical symptoms selected based on the report from Ministry of Health and Welfare, Korea. Technically, our system uses a modified FCM for clustering diseases and the input vector consists of the result of user-selected questionnaires. Our modified FCM improves the quality of clusters by applying symmetry measure based on the fuzzy theory so that the clusters are relatively insensitive to the shape of the pattern distribution. Furthermore, we extract the highest 5 diseases only related to the user-selected questionnaires based on the fuzzy membership function between questionnaires and diseases in order to avoid diagnosing unrelated disease.