Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees...

Descripción completa

Detalles Bibliográficos
Autores principales: Chou, Hsiu-Ling, Yao, Chung-Tay, Su, Sui-Lun, Lee, Chia-Yi, Hu, Kuang-Yu, Terng, Harn-Jing, Shih, Yun-Wen, Chang, Yu-Tien, Lu, Yu-Fen, Chang, Chi-Wen, Wahlqvist, Mark L, Wetter, Thomas, Chu, Chi-Ming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614553/
https://www.ncbi.nlm.nih.gov/pubmed/23506640
http://dx.doi.org/10.1186/1471-2105-14-100

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614553/
https://www.ncbi.nlm.nih.gov/pubmed/23506640
http://dx.doi.org/10.1186/1471-2105-14-100

Ejemplares similares