Breast cancer survivability prediction using labeled, unlabeled, and pseudo-labeled patient data

Author:

Kim Juhyeon,Shin Hyunjung

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference32 articles.

1. American Cancer Society. Cancer Facts & Figures 2010. Atlanta: American Cancer Society, 2010.

2. National Cancer Institute. Breast Cancer Statistics, USA, 2010, National Cancer Institute, 2010. http://www.cancer.gov/cancertopics/types/breast (accessed: 11 Jul 2011).

3. Improved breast cancer prognosis through the combination of clinical and genetic markers

4. Khan U Shin H Choi JP . wFDT—Weighted Fuzzy decision trees for prognosis of breast cancer survivability. In: Roddick JF Li J Christen P Kennedy PJ , eds. Proceedings of the Seventh Australasian Data Mining Conference. Glenelg, South Australia, 2008:141–52.

5. Predicting breast cancer survivability: a comparison of three data mining methods

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