Fuzzy Rule Extraction from Nursing-Care Texts

机译：从护理文本中提取模糊规则

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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.

机译：护理质量的提高对我们的生活非常重要。当前，通过使用Web应用程序从日本许多医院收集了护理自由式文本（护理数据）。收集的护理数据被存储到数据库中。为了评估护理数据，我们已经提出了模糊分类系统，基于神经网络的系统，基于支持向量机（SVM）的分类系统。然后，为了提高分类性能，提出了一种基于遗传算法的特征选择方法，用于从采集的护理文本中生成数值数据。本文提出了一种从护理中提取模糊规则的方法文字数据。首先，通过基于遗传算法的特征选择方法选择护理文本的特征。接下来，使用选定的特征生成数字训练数据。然后，我们使用生成的训练数据训练神经网络。最后，通过并行化规则提取方法从训练后的神经网络中提取出模糊的if-then规则。从计算机仿真结果来看，该方法是有效的。

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来源
《Multiple-Valued Logic, 2009. ISMVL '09》|2009年|30-35|共6页
会议地点 Naha(JP);Naha(JP)
作者
Nii M.; Yamaguchi T.; Takahashi Y.; Uchinuno A.; Sakashita R.;
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Grad. Sch. of Eng., Univ. of Hyogo, Himeji;

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fuzzy reasoning; genetic algorithms; health care; learning (artificial intelligence); medical computing; neural nets; pattern classification; text analysis; feature selection method; fuzzy if-then rule; fuzzy rule extraction; genetic algorithm; neural network training; numerical training data; nursing-care text data classification;

机译：模糊推理;遗传算法;卫生保健;学习（人工智能）;医学计算;神经网络;模式分类;文本分析;特征选择方法;模糊if-then规则;模糊规则提取;遗传算法;神经网络训练;数值训练数据;护理文本数据分类;

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专利

1. Rules and fuzzy rules in text: concept, extraction and usage [J] . D.H. Kraft, J. Chen, M. J. Martin-Bautista, Operations Research . 2004,第3期

机译：文本中的规则和模糊规则：概念，提取和用法
2. Rules and fuzzy rules in text: concept, extraction and usage [J] . D.H. Kraft, M.J. Martin-Bautista, J. Chen, International Journal of Approximate Reasoning . 2003,第2a3期

机译：文本中的规则和模糊规则：概念，提取和用法
3. Improving Classification Performance of Nursing-Care Text Classification System by Using GA-Based Term Selection [J] . Manabu Nii, Takafumi Yamaguchi, Yutaka Takahashi, Journal of Advanced Computatioanl Intelligence and Intelligent Informatics . 2010,第2a74期

机译：利用基于GA的术语选择提高护理文本分类系统的分类性能
4. Fuzzy Rule Extraction from Nursing-care Texts [C] . Manabu Nii, Takafumi Yamaguchi, Yutaka Takahashi, IEEE International Symposium on Multiple-Valued Logic . 2009

机译：从护理文本提取的模糊规则提取
5. Optimal data-driven rule extraction using adaptive fuzzy-neural models. [D] . Gaweda, Adam Edward. 2002

机译：使用自适应模糊神经模型的最佳数据驱动规则提取。
6. DEFINDER: Rule-based Methods for the Extraction of Medical Terminology and their Associated Definitions from On-line Text [O] . Judith L. Klavans, Smaranda Muresan 2000

机译：定义：从在线文本中提取医学术语及其相关定义的基于规则的方法
7. Rules and fuzzy rules in text: concept, extraction and usage [O] . Kraft D.H., Martı́n-Bautista M.J., Chen J., 2003

机译：文本中的规则和模糊规则：概念，提取和用法
8. Measuring uncertainty by extracting fuzzy rules using rough sets and extracting fuzzy rules under uncertainty and measuring definability using rough sets [R] . Worm, Jeffrey A., Culas, Donald E. 1991

机译：通过粗糙集提取模糊规则并在不确定条件下提取模糊规则并使用粗糙集测量可定义性来测量不确定性

Fuzzy Rule Extraction from Nursing-Care Texts

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