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Fuzzy Rule Extraction from Nursing-Care Texts

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5 Author(s)
Nii, M. ; Grad. Sch. of Eng., Univ. of Hyogo, Himeji ; Yamaguchi, T. ; Takahashi, Y. ; Uchinuno, A.
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The nursing care quality improvement is very important for our life. Currently, nursing-care freestyle texts (nursing-care data) are collected from many hospitals in Japan by using Web applications. The collected nursing-care data are stored into the database. To evaluate nursing-care data, we have already proposed a fuzzy classification system, a neural network based system, a support vector machine (SVM) based classification system. Then, in order to improve the classification performance, we have proposed a genetic algorithm (GA) based feature selection method for generating numerical data from collected nursing-care texts.In this paper, we propose a fuzzy rule extraction method from the nursing-care text data. First, features of nursing-care texts are selected by a genetic algorithm based feature selection method. Next, numerical training data are generated by using selected features. Then we train neural networks using generated training data. Finally, fuzzy if-then rules are extracted from the trained neural networks by the parallelized rule extraction method.From computer simulation results, we show the effectiveness of our proposed method.

Published in:

Multiple-Valued Logic, 2009. ISMVL '09. 39th International Symposium on

Date of Conference:

21-23 May 2009