Survival prediction and feature selection in patients with breast cancer using support vector regression

DOI10.1155/2016/2157984zbMath1423.92085DBLPjournals/cmmm/GoliMFMS16OpenAlexW2547143277WikidataQ37413643 ScholiaQ37413643MaRDI QIDQ2011730

Javad Faradmal, Shahrbanoo Goli, Hoda Mashayekhi, Hossein Mahjub, Ali-Reza Soltanian

Publication date: 4 August 2017

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2016/2157984

zbMATH Keywords

breast cancersupport vector regressionsurvival prediction

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Medical applications (general) (92C50) Computational methods for problems pertaining to biology (92-08)

Uses Software

• SVRc

Cites Work

• Modeling survival data: extending the Cox model
• Survival analysis. Techniques for censored and truncated data.
• Optimal feature selection for support vector machines
• 10.1162/153244303322753616
• 10.1162/153244303322753715
• Gene selection for cancer classification using support vector machines
• Unnamed Item

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