학술논문
Predicting the survivability of breast cancer patients using ensemble approach
Document Type
Conference
Author
Source
2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT) Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on. :459-464 Feb, 2014
Subject
Language
Abstract
Data mining in healthcare is one of most preferable research field in these days. In healthcare, data are coming from different sources and are continuously stored in data repositories. Healthcare organization generates vast amount of data which contains useful information. Data Mining is used for uncovering the valuable information from medical data which in turn helpful for making important decision regarding patient's health. This paper used breast cancer data from SEER (Surveillance of Epidemiology and End Result) which is contributed by National Cancer Institute. The dataset consists data of various types of cancer such as breast, lung, oral cancer etc. The proposed research work first analyzes the breast cancer dataset and then applying data mining approach to evaluate the results. Data Mining is used for getting the patterns of the disease which can be effectively utilized by medical practitioner. For predicting the survivability of breast cancer patients an ensemble classification approach is presented in this paper.