Modified Logistic Regression Models Using Gene Coexpression and Clinical Features to Predict Prostate Cancer Progression

Predicting disease progression is one of the most challenging problems in prostate cancer research. Adding gene expression data to prediction models that are based on clinical features has been proposed to improve accuracy. In the current study, we applied a logistic regression (LR) model combining...

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Detalles Bibliográficos
Autores principales: Zhao, Hongya, Logothetis, Christopher J., Gorlov, Ivan P., Zeng, Jia, Dai, Jianguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866878/
https://www.ncbi.nlm.nih.gov/pubmed/24367394
http://dx.doi.org/10.1155/2013/917502

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866878/
https://www.ncbi.nlm.nih.gov/pubmed/24367394
http://dx.doi.org/10.1155/2013/917502

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