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An Intelligent System Approach for Asthma Prediction in Symptomatic Preschool Children
Joint Authors
Chatzimichail, E.
Rigas, A.
Paraskakis, E.
Sitzimi, M.
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-14
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Objectives.
In this study a new method for asthma outcome prediction, which is based on Principal Component Analysis and Least Square Support Vector Machine Classifier, is presented.
Most of the asthma cases appear during the first years of life.
Thus, the early identification of young children being at high risk of developing persistent symptoms of the disease throughout childhood is an important public health priority.
Methods.
The proposed intelligent system consists of three stages.
At the first stage, Principal Component Analysis is used for feature extraction and dimension reduction.
At the second stage, the pattern classification is achieved by using Least Square Support Vector Machine Classifier.
Finally, at the third stage the performance evaluation of the system is estimated by using classification accuracy and 10-fold cross-validation.
Results.
The proposed prediction system can be used in asthma outcome prediction with 95.54 % success as shown in the experimental results.
Conclusions.
This study indicates that the proposed system is a potentially useful decision support tool for predicting asthma outcome and that some risk factors enhance its predictive ability.
American Psychological Association (APA)
Chatzimichail, E.& Paraskakis, E.& Sitzimi, M.& Rigas, A.. 2013. An Intelligent System Approach for Asthma Prediction in Symptomatic Preschool Children. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-456515
Modern Language Association (MLA)
Chatzimichail, E.…[et al.]. An Intelligent System Approach for Asthma Prediction in Symptomatic Preschool Children. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-456515
American Medical Association (AMA)
Chatzimichail, E.& Paraskakis, E.& Sitzimi, M.& Rigas, A.. An Intelligent System Approach for Asthma Prediction in Symptomatic Preschool Children. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-456515
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-456515