Predicting prostate cancer progression with penalized logistic regression model based on co-expressed genes.
Hongya ZhaoSongru QiQi DongPublished in: BMEI (2012)
Keyphrases
- logistic regression
- prostate cancer
- loss function
- disease progression
- prognostic models
- computer aided
- breast cancer
- decision trees
- gene expression
- mr images
- support vector
- logistic regression models
- magnetic resonance spectroscopy
- naive bayes
- medical image analysis
- cancer patients
- maximum likelihood
- gene expression data
- microarray data
- least squares
- fold cross validation
- learning algorithm
- gene expression profiles
- pairwise
- deformable models
- model selection
- gene selection
- survival analysis
- image processing