Title :
Predicting breast cancer recurrence using data mining techniques
Author :
Fan, Qi ; Zhu, Chang-Jie ; Yin, Liu
Author_Institution :
Dept. of Comput. Sci., Huaibei Coal Ind. Teacher Coll., Huaibei, China
Abstract :
In this study, we firstly take good advantage of SEER Public-Use Data to predict breast cancer recurrence using data mining techniques. The SEER Public-Use Data 2005 is used in this research. We presented a new data pre-classification method and firstly find a possible solution to discover the information of breast cancer recurrence of SEER data. After the preprocessing of the dataset, we investigate several algorithms. As a result, we found c5 algorithm has the best performance of accuracy.
Keywords :
biological tissues; cancer; data mining; medical computing; pattern classification; SEER public use data 2005; breast cancer recurrence prediction; c5 algorithm; data mining techniques; data preclassification method; Breast cancer; Computer industry; Computer science; Data mining; Diffusion tensor imaging; Educational institutions; Hospitals; Medical diagnostic imaging; Mining industry; Testing; Breast Cancer Recurrence; Data Mining; SEER;
Conference_Titel :
Bioinformatics and Biomedical Technology (ICBBT), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6775-4
DOI :
10.1109/ICBBT.2010.5478952
