太阳成8722(中国)有限公司-GREEN NO.1

标题：Application of Entropy-Based Attribute Reduction and an Artificial Neural Network in Medicine: A Case Study of Estimating Medical Care Costs Associated with Myocardial Infarction作者：Du, Qingyun; Nie, Ke; Wang, Zhensheng

来源出版物：ENTROPY 卷：16 期：9 页：4788-4800 DOI：10.3390/e16094788 出版年：SEP 2014

摘要：In medicine, artificial neural networks (ANN) have been extensively applied in many fields to model the nonlinear relationship of multivariate data. Due to the difficulty of selecting input variables, attribute reduction techniques were widely used to reduce data to get a smaller set of attributes. However, to compute reductions from heterogeneous data, a discretizing algorithm was often introduced in dimensionality reduction methods, which may cause information loss. In this study, we developed an integrated method for estimating the medical care costs, obtained from 798 cases, associated with myocardial infarction disease. The subset of attributes was selected as the input variables of ANN by using an entropy-based information measure, fuzzy information entropy, which can deal with both categorical attributes and numerical attributes without discretization. Then, we applied a correction for the Akaike information criterion (AIC(C)) to compare the networks. The results revealed that fuzzy information entropy was capable of selecting input variables from heterogeneous data for ANN, and the proposed procedure of this study provided a reasonable estimation of medical care costs, which can be adopted in other fields of medical science.

入藏号：WOS:000343110100004

文献类型：Article

语种：English

作者关键词：artificial neural network, fuzzy information entropy, medical costs estimation, myocardial infarction disease, attribute reduction

扩展关键词：DIMENSIONALITY REDUCTION; MODEL SELECTION; ROUGH; DIAGNOSIS; ALGORITHM

通讯作者地址：Wang, Zhensheng; Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

电子邮件地址：qydu@whu.edu.cn; nieke@whu.edu.cn; wangzhens@whu.edu.cn

地址：

[Du, Qingyun; Nie, Ke; Wang, Zhensheng]Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.

[Du, Qingyun; Nie, Ke; Wang, Zhensheng] Wuhan Univ, Minist Educ, Key Lab GIS, Wuhan 430079, Peoples R China.

研究方向：Physics

ISSN：1099-4300