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» A Clustering-Based Approach to Predict Outcome in Cancer Pat...
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IEAAIE
2010
Springer
13 years 4 months ago
Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles
Abstract. Gene expression profiling strategies have attracted considerable interest from biologist due to the potential for high throughput analysis of hundreds of thousands of gen...
Daniel Urda, José Luis Subirats, Leonardo F...
PSB
2008
13 years 7 months ago
Integration of Microarray and Textual Data Improves the Prognosis Prediction of Breast, Lung, and Ovarian Cancer Patients
bstracts in the structure prior of a Bayesian network could improve the prediction of the prognosis in cancer. Our results show that prediction of the outcome with the text prior w...
O. Gaevert, Steven Van Vooren, Bart De Moor
BMCBI
2010
149views more  BMCBI 2010»
13 years 6 months ago
Identifying common prognostic factors in genomic cancer studies: A novel index for censored outcomes
Background: With the growing number of public repositories for high-throughput genomic data, it is of great interest to combine the results produced by independent research groups...
Sigrid Rouam, Thierry Moreau, Philippe Broët
BMCBI
2010
123views more  BMCBI 2010»
13 years 6 months ago
Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context
Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...
BMCBI
2004
180views more  BMCBI 2004»
13 years 6 months ago
Noise filtering and nonparametric analysis of microarray data underscores discriminating markers of oral, prostate, lung, ovaria
Background: A major goal of cancer research is to identify discrete biomarkers that specifically characterize a given malignancy. These markers are useful in diagnosis, may identi...
Virginie M. Aris, Michael J. Cody, Jeff Cheng, Jam...