A gene signature for breast cancer prognosis using support vector machine

• Published in: 2012 5th International Conference on Biomedical Engineering and Informatics pp. 928 - 931
• Main Authors: Xu, Xiaoyi, Zhang, Ya, Zou, Liang, Wang, Minghui, Li, Ao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2012
• Subjects: Accuracy; Breast cancer; Feature extraction; feature selection; Gene expression; gene signature; Machine learning algorithms; Nearest neighbor methods; Prediction algorithms; Prognostics and health management; support vector machine; Support vector machines; Vectors

Breast cancer is a common disease in elderly women. With the development of microarray technique, discovering gene signature became a powerful approach in predicting survival of breast cancer. Previously, a 70-gene signature had been discovered for breast cancer prognosis prediction and received a g...