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ICMLA
2008
13 years 9 months ago
A Clustering Approach in Developing Prognostic Systems of Cancer Patients
Accurate prediction of survival rates of cancer patients is often key to stratify patients for prognosis and treatment. Survival prediction is often accomplished by the TNM system...
Dechang Chen, Kai Xing, Donald Henson, Li Sheng, A...
BMCBI
2010
95views more  BMCBI 2010»
13 years 7 months ago
Modelling p-value distributions to improve theme-driven survival analysis of cancer transcriptome datasets
Background: Theme-driven cancer survival studies address whether the expression signature of genes related to a biological process can predict patient survival time. Although this...
Esteban Czwan, Benedikt Brors, David Kipling
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 8 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
BMCBI
2007
182views more  BMCBI 2007»
13 years 7 months ago
Additive risk survival model with microarray data
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...
Shuangge Ma, Jian Huang
BMCBI
2010
127views more  BMCBI 2010»
13 years 7 months ago
SplicerAV: a tool for mining microarray expression data for changes in RNA processing
Background: Over the past two decades more than fifty thousand unique clinical and biological samples have been assayed using the Affymetrix HG-U133 and HG-U95 GeneChip microarray...
Timothy J. Robinson, Michaela A. Dinan, Mark Dewhi...