A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
Derivation of molecular signatures for breast cancer recurrence prediction using a two-way validation approach
2009
Breast Cancer Research and Treatment
Previous studies have demonstrated the potential value of gene expression signatures in assessing the risk of post-surgical breast cancer recurrence, however, many of these predictive models have been derived using simple computational algorithms and validated internally or using one-way validation on a single dataset. We have recently developed a new feature selection algorithm that overcomes some limitations inherent to high-dimensional data analysis. In this study, we applied this algorithm
doi:10.1007/s10549-009-0365-6
pmid:19291396
pmcid:PMC2844120
fatcat:tsjqjzewhndhlajoi4goi2msdu