Breast cancer survivability via AdaBoost algorithms
HDKM '08 Proceedings of the second Australasian workshop on Health data and knowledge management - Volume 80
Support Vector Machine for Outlier Detection in Breast Cancer Survivability Prediction
Advanced Web and NetworkTechnologies, and Applications
Toward breast cancer survivability prediction models through improving training space
Expert Systems with Applications: An International Journal
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Since early 1980's, the rapid growth of hospital information systems (HIS) stores the large amount of laboratory examinations as databases. Thus, it is highly expected that data mining methods will find interesting patterns from databases as reuse of stored data and be important for medical research and practice because human beings cannot deal with such a huge amount of data. In this paper, we focus on the characteristics of medical data and discuss how data miners deal with medical data.