title: Predicting 5-Year Survival Status of Patients with Breast Cancer based on Supervised Wavelet Method.
abstract: OBJECTIVE
  Classification of breast cancer patients into different risk classes is very important in clinical applications. It is estimated that the advent of high-dimensional gene expression data could improve patient classification. In this study, a new method for transforming the high-dimensional gene expression data in a low-dimensional space based on wavelet transform (WT) is presented.
  
  
  METHODS
  The proposed method was applied to three publicly available microarray data sets. After dimensionality reduction using supervised wavelet, a predictive support vector machine (SVM) model was built upon the reduced dimensional space. In addition, the proposed method was compared with the supervised principal component analysis (PCA).
  
  
  RESULTS
  The performance of supervised wavelet and supervised PCA based on selected genes were better than the signature genes identified in the other studies. Furthermore, the supervised wavelet method generally performed better than the supervised PCA for predicting the 5-year survival status of patients with breast cancer based on microarray data. In addition, the proposed method had a relatively acceptable performance compared with the other studies.
  
  
  CONCLUSIONS
  The results suggest the possibility of developing a new tool using wavelets for the dimension reduction of microarray data sets in the classification framework.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
authors.forename: Maryam
authors.initials: M
authors.lastname: Farhadian
authors.affiliation: Research Center for Health Sciences and Department of Epidemiology and Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
authors.forename: Hossein
authors.initials: H
authors.lastname: Mahjub
authors.affiliation: Modeling of Noncommunicable Diseases Research Center, Department of Epidemiology and Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
authors.forename: Jalal
authors.initials: J
authors.lastname: Poorolajal
authors.affiliation: Modeling of Noncommunicable Disease Research Center, Department of Biostatistics and Epidemiology, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
authors.forename: Abbas
authors.initials: A
authors.lastname: Moghimbeigi
authors.affiliation: Department of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamadan, Iran.
authors.forename: Muharram
authors.initials: M
authors.lastname: Mansoorizadeh
keywords: breast cancer; microarray data; supervised wavelet; support vector machine