Associative Memory using Cellular Neural Networks and its Application to Medical Diagnosis

Abstract

It is very difficult to realize medical diagnosis systems on a computer, because in order to judge many sick support groups synthetically, generally one needs to use the data that consists of dozens or more items (the amount of the features). In this paper, a computer-aided medical diagnostic system is constructed using the Three-valued Cellular Neural Network (T-CNN), which has achieved excellent results in pattern classification, and the classification capability is examined by using liver disease data as an example. Consequently, a comparatively good diagnostic result is obtained from the T-CNN under the conditions examined by this study. Because the T-CNN can realize a system which performs the judging comparatively near humans, and tends to utilize the features of the whole sickness pattern, it was concluded that it could perform judgment nearest to the overall judgment by a specialist.