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Comparison of Classification Algorithms with Wrapper-Based Feature Selection for Predicting Osteoporosis Outcome Based on Genetic Factors in a Taiwanese Women Population
Joint Authors
Chang, Hsueh-Wei
Ho, Wen-Hsien
Chiu, Yu-Hsien
Kao, Hao-Yun
Yang, Cheng-Hong
Source
International Journal of Endocrinology
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-01-14
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
An essential task in a genomic analysis of a human disease is limiting the number of strongly associated genes when studying susceptibility to the disease.
The goal of this study was to compare computational tools with and without feature selection for predicting osteoporosis outcome in Taiwanese women based on genetic factors such as single nucleotide polymorphisms (SNPs).
To elucidate relationships between osteoporosis and SNPs in this population, three classification algorithms were applied: multilayer feedforward neural network (MFNN), naive Bayes, and logistic regression.
A wrapper-based feature selection method was also used to identify a subset of major SNPs.
Experimental results showed that the MFNN model with the wrapper-based approach was the best predictive model for inferring disease susceptibility based on the complex relationship between osteoporosis and SNPs in Taiwanese women.
The findings suggest that patients and doctors can use the proposed tool to enhance decision making based on clinical factors such as SNP genotyping data.
American Psychological Association (APA)
Chang, Hsueh-Wei& Chiu, Yu-Hsien& Kao, Hao-Yun& Yang, Cheng-Hong& Ho, Wen-Hsien. 2013. Comparison of Classification Algorithms with Wrapper-Based Feature Selection for Predicting Osteoporosis Outcome Based on Genetic Factors in a Taiwanese Women Population. International Journal of Endocrinology،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-503249
Modern Language Association (MLA)
Chang, Hsueh-Wei…[et al.]. Comparison of Classification Algorithms with Wrapper-Based Feature Selection for Predicting Osteoporosis Outcome Based on Genetic Factors in a Taiwanese Women Population. International Journal of Endocrinology No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-503249
American Medical Association (AMA)
Chang, Hsueh-Wei& Chiu, Yu-Hsien& Kao, Hao-Yun& Yang, Cheng-Hong& Ho, Wen-Hsien. Comparison of Classification Algorithms with Wrapper-Based Feature Selection for Predicting Osteoporosis Outcome Based on Genetic Factors in a Taiwanese Women Population. International Journal of Endocrinology. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-503249
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-503249