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Breast cancer prognosis risk estimation using integrated gene expression and clinical data

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Version 2 2024-06-03, 12:09
Version 1 2014-11-25, 23:33
journal contribution
posted on 2024-06-03, 12:09 authored by A Saini, Jingyu HouJingyu Hou, W Zhou
Novel prognostic markers are needed so newly diagnosed breast cancer patients do not undergo any unnecessary therapy. Various microarray gene expression datasets based studies have generated gene signatures to predict the prognosis outcomes, while ignoring the large amount of information contained in established clinical markers. Nevertheless, small sample sizes in individual microarray datasets remain a bottleneck in generating robust gene signatures that show limited predictive power. The aim of this study is to achieve high classification accuracy for the good prognosis group and then achieve high classification accuracy for the poor prognosis group.

History

Journal

BioMed research international

Volume

2014

Article number

459203

Pagination

1-15

Location

United States

Open access

  • Yes

ISSN

2314-6133

eISSN

2314-6141

Language

eng

Publication classification

C Journal article, C1 Refereed article in a scholarly journal

Copyright notice

2014, Hindawi Publishing Corporation

Publisher

Hindawi Publishing Corporation