DocumentCode
121771
Title
Predicting the survivability of breast cancer patients using ensemble approach
Author
Rathore, Nisha ; Tomar, Divya ; Agarwal, Sankalp
Author_Institution
Software Eng., Indian Inst. of Inf. Technol., Allahabad, India
fYear
2014
fDate
7-8 Feb. 2014
Firstpage
459
Lastpage
464
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.
Keywords
cancer; data mining; decision making; diseases; health care; pattern classification; National Cancer Institute; SEER; Surveillance of Epidemiology and End Result; breast cancer patients survivability prediction; data mining; data repositories; decision making; disease; ensemble classification approach; healthcare organization; medical data; Accuracy; Breast; Computational modeling; Lymph nodes; Silicon; Surgery; Breast Cancer; Data Mining; Ensemble Classifier; Healthcare; SEER;
fLanguage
English
Publisher
ieee
Conference_Titel
Issues and Challenges in Intelligent Computing Techniques (ICICT), 2014 International Conference on
Conference_Location
Ghaziabad
Type
conf
DOI
10.1109/ICICICT.2014.6781326
Filename
6781326
Link To Document