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The Scientific World Journal
Volume 2013, Article ID 475702, 5 pages
http://dx.doi.org/10.1155/2013/475702
Research Article

Adaptive Shooting Regularization Method for Survival Analysis Using Gene Expression Data

1Faculty of Information Technology & State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Macau 999078, China
2Faculty of Science, Xi’an Jiaotong University, Xi’an 710000, China
3Department of Computer Science and Technology, The Chinese University of Hong Kong, Hong Kong 999077, China

Received 3 September 2013; Accepted 30 October 2013

Academic Editors: J. Ma, B. Shen, J. Wang, and J. Wang

Copyright © 2013 Xiao-Ying Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • Maryam Farhadian, Paulo J. G. Lisboa, Abbas Moghimbeigi, Jalal Poorolajal, and Hossein Mahjub, “Supervised Wavelet Method to Predict Patient Survival from Gene Expression Data,” The Scientific World Journal, vol. 2014, pp. 1–10, 2014. View at Publisher · View at Google Scholar
  • Hyokyoung G. Hong, Jian Kang, and Yi Li, “Conditional screening for ultra-high dimensional covariates with survival outcomes,” Lifetime Data Analysis, 2016. View at Publisher · View at Google Scholar
  • Yi Liu, and Xiaolin Chen, “Quantile screening for ultra-high-dimensional heterogeneous data conditional on some variables,” Journal of Statistical Computation and Simulation, pp. 1–14, 2017. View at Publisher · View at Google Scholar