Developing a Prognostic Gene Panel of Epithelial Ovarian Cancer Patients by a Machine Learning Model

Developing a Prognostic Gene Panel of Epithelial Ovarian Cancer Patients by a Machine Learning Model

Epithelial ovarian cancer patients usually relapse after primary management. We utilized the support vector machine algorithm to develop a model for the chemo-response using the Cancer Cell Line Encyclopedia (CCLE) and validated the model in The Cancer Genome Atlas (TCGA) and the GSE9891 dataset. Fi...

Full description

Bibliographic Details
Main Authors: Tzu-Pin Lu, Kuan-Ting Kuo, Ching-Hsuan Chen, Ming-Cheng Chang, Hsiu-Ping Lin, Yu-Hao Hu, Ying-Cheng Chiang, Wen-Fang Cheng, Chi-An Chen
Format: Article
Language:English
Published: MDPI AG 2019-02-01
Series:Cancers
Subjects:
chemotherapy
microarray
ovarian cancer
predictive model
machine learning
Online Access:https://www.mdpi.com/2072-6694/11/2/270

Internet

https://www.mdpi.com/2072-6694/11/2/270

Similar Items