Association Rule Mining Based Predicting Breast Cancer Recurrence on SEER Breast Cancer Data

被引：0
作者：
Umesh, D. R. [1 ]
Ramachandra, B. [2 ]
机构：
[1] PESCE, PET Res Ctr, Mandya, Karnataka, India
[2] PESCE, Dept Elect & Elect, Mandya, Karnataka, India
来源：
2015 INTERNATIONAL CONFERENCE ON EMERGING RESEARCH IN ELECTRONICS, COMPUTER SCIENCE AND TECHNOLOGY (ICERECT) | 2015年
关键词：
Association rule mining; Breast cancer; Recurrence; SEER Dataset;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Breast cancer is the most well-known type of cancer in women in the developed nations including India. Breast cancer could recur anytime in the breast cancer survivors, however basically it returns in the initial three to five years after the treatment. In this paper we investigate the feasibility of utilizing an association rule mining for a clinical oncology doctor in expectation of breast cancer recurrence on SEER (Surveillance, Epidemiology, and End Results) dataset.
引用
收藏
页码：376 / 380
页数：5
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