A multilayer perceptron-based medical decision support system for heart disease diagnosis

The medical diagnosis by nature is a complex and fuzzy cognitive process, and soft computing methods, such as neural networks, have shown great potential to be applied in the development of medical decision support systems (MDSS). In this paper, a multiplayer perceptron-based decision support system...

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Published in:	Expert systems with applications Vol. 30; no. 2; pp. 272 - 281
Main Authors:	Yan, Hongmei, Jiang, Yingtao, Zheng, Jun, Peng, Chenglin, Li, Qinghui
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.02.2006
Subjects:	Back propagation algorithm Heart disease Medical decision support system Multilayer perceptron Performance of classifier Medical decision support system Multilayer perceptron Back propagation algorithm Performance of classifier Heart disease
ISSN:	0957-4174, 1873-6793
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Abstract	The medical diagnosis by nature is a complex and fuzzy cognitive process, and soft computing methods, such as neural networks, have shown great potential to be applied in the development of medical decision support systems (MDSS). In this paper, a multiplayer perceptron-based decision support system is developed to support the diagnosis of heart diseases. The input layer of the system includes 40 input variables, categorized into four groups and then encoded using the proposed coding schemes. The number of nodes in the hidden layer is determined through a cascade learning process. Each of the 5 nodes in the output layer corresponds to one heart disease of interest. In the system, the missing data of a patient are handled using the substituting mean method. Furthermore, an improved back propagation algorithm is used to train the system. A total of 352 medical records collected from the patients suffering from five heart diseases have been used to train and test the system. In particular, three assessment methods, cross validation, holdout and bootstrapping, are applied to assess the generalization of the system. The results show that the proposed MLP-based decision support system can achieve very high diagnosis accuracy (>90%) and comparably small intervals (<5%), proving its usefulness in support of clinic decision process of heart diseases.
AbstractList	The medical diagnosis by nature is a complex and fuzzy cognitive process, and soft computing methods, such as neural networks, have shown great potential to be applied in the development of medical decision support systems (MDSS). In this paper, a multiplayer perceptron-based decision support system is developed to support the diagnosis of heart diseases. The input layer of the system includes 40 input variables, categorized into four groups and then encoded using the proposed coding schemes. The number of nodes in the hidden layer is determined through a cascade learning process. Each of the 5 nodes in the output layer corresponds to one heart disease of interest. In the system, the missing data of a patient are handled using the substituting mean method. Furthermore, an improved back propagation algorithm is used to train the system. A total of 352 medical records collected from the patients suffering from five heart diseases have been used to train and test the system. In particular, three assessment methods, cross validation, holdout and bootstrapping, are applied to assess the generalization of the system. The results show that the proposed MLP-based decision support system can achieve very high diagnosis accuracy (>90%) and comparably small intervals (<5%), proving its usefulness in support of clinic decision process of heart diseases.
Author	Jiang, Yingtao Li, Qinghui Yan, Hongmei Zheng, Jun Peng, Chenglin
Author_xml	– sequence: 1 givenname: Hongmei surname: Yan fullname: Yan, Hongmei email: hmyan@uestc.edu.cn organization: Life Science and Technology Institute, University of Electronic Science and Technology of China, Chengdu, Peoples's Republic of China 610054 – sequence: 2 givenname: Yingtao surname: Jiang fullname: Jiang, Yingtao email: yingtao@egr.unlv.edu organization: Department of Electrical and Computer Engineering, University of Nevada, Las Vegas, Las Vegas, NV 89154, USA – sequence: 3 givenname: Jun surname: Zheng fullname: Zheng, Jun email: zheng@cs.qc.edu organization: Department of Computer Science, Queens College-City University of New York, Flushing, NY 11367, USA – sequence: 4 givenname: Chenglin surname: Peng fullname: Peng, Chenglin organization: Bioengineering Institute, Chongqing University, Chongqing, Peoples's Republic of China 400044 – sequence: 5 givenname: Qinghui surname: Li fullname: Li, Qinghui organization: Southwest Hospital, Chongqing, Peoples's Republic of China 400038
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SubjectTerms	Back propagation algorithm Heart disease Medical decision support system Multilayer perceptron Performance of classifier
Title	A multilayer perceptron-based medical decision support system for heart disease diagnosis
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