Abstract
Fuzzy inference has been applied for various types of clinical diagnosis, such as computer-aided diagnosis. Most of clinicians, however, tend to hesitate to adopt it, because some difficulties are inevitable to apply fuzzy inference actually. Although there are some certain ways of thinking in clinical diagnosis, clinicians cannot transform them to fuzzy production rule in most cases. For general clinicians, it is very complicated to generate and prepare the membership functions. Consequently, computer-aided diagnosis using fuzzy inference is hardly to be applicable in clinical field. Therefore, the authors would like to propose the adaptive neuro-fuzzy inference system (ANFIS) for the construction of computer-aided diagnosis system. Using ANFIS, the membership functions can be adjusted adequately in neural-network principle from retrospective clinical data. Then, clinicians do not have to generate and verify the membership functions critically. In this paper, we report the attempt of ANFIS to ultrasonographic diagnosis and indicate its validity for diagnostic aid.
