A classification capability of Reflective Neural Networks in medical databases

Abstract

Medical database recorded diagnostic information based on a patient's medical card. However, each card does not fulfill all the required information for learning algorithm. Reflective Neural Network has an outstanding classification capability, even if such records with shortage exist in a set of training cases. Reflective Neural Network is based on the network module concept. There are two kinds of network modules; an allocation module to distribute a training case and some classification modules to classify a subset of training cases. Each classification module consists of a monitor neural network and a worker neural network. The monitor neural network estimates how conformable the worker neural network is to a given training case. Moreover, the training case is distributed over different classification modules. These classification modules compete with each other in the classification task. In this paper, we report the classification capability in a medical database on the patients in ICUs.