Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
It is very important to improve the nursing care quality in a medical field. Currently, nursing-care data are collected via WWW from many hospitals in Japan. The collected data are stored into a database. Some nursing-care experts evaluate the collected data to improve nursing care quality. However, it is difficult for experts to evaluate the data because of huge number of nursing-care data in the database. In order to reduce workloads to evaluate nursing-care data, we propose a neural network based classification system. We use standard three-layer feedforward neural networks with backpropagation type learning. First, we extract attribute values from texts written by nurses for generating numerical training data. And then, we train a neural network using the training data. From computer simulations, we show the effectiveness of our proposed system.
