![](/images/graphics-bg.png)
Supervised Wavelet Method to Predict Patient Survival from Gene Expression Data
Joint Authors
Lisboa, Paolo
Farhadian, Maryam
Moghimbeigi, Abbas
Poorolajal, Jalal
Mahjub, Hossein
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-11-03
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
In microarray studies, the number of samples is relatively small compared to the number of genes per sample.
An important aspect of microarray studies is the prediction of patient survival based on their gene expression profile.
This naturally calls for the use of a dimension reduction procedure together with the survival prediction model.
In this study, a new method based on combining wavelet approximation coefficients and Cox regression was presented.
The proposed method was compared with supervised principal component and supervised partial least squares methods.
The different fitted Cox models based on supervised wavelet approximation coefficients, the top number of supervised principal components, and partial least squares components were applied to the data.
The results showed that the prediction performance of the Cox model based on supervised wavelet feature extraction was superior to the supervised principal components and partial least squares components.
The results suggested the possibility of developing new tools based on wavelets for the dimensionally reduction of microarray data sets in the context of survival analysis.
American Psychological Association (APA)
Farhadian, Maryam& Lisboa, Paolo& Moghimbeigi, Abbas& Poorolajal, Jalal& Mahjub, Hossein. 2014. Supervised Wavelet Method to Predict Patient Survival from Gene Expression Data. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1050361
Modern Language Association (MLA)
Farhadian, Maryam…[et al.]. Supervised Wavelet Method to Predict Patient Survival from Gene Expression Data. The Scientific World Journal No. 2014 (2014), pp.1-10.
https://search.emarefa.net/detail/BIM-1050361
American Medical Association (AMA)
Farhadian, Maryam& Lisboa, Paolo& Moghimbeigi, Abbas& Poorolajal, Jalal& Mahjub, Hossein. Supervised Wavelet Method to Predict Patient Survival from Gene Expression Data. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-10.
https://search.emarefa.net/detail/BIM-1050361
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050361