A Comparitive Survey on Data Mining Techniques for Breast Cancer Diagnosis and Prediction
نویسنده
چکیده
Breast cancer is one of the deadliest diseases, is the most common of all cancers and is the leading cause of cancer deaths in women worldwide. The classification of Breast Cancer data can be useful to predict the outcome of some diseases or discover the genetic behavior of tumors. In this paper we present a comparative survey on data mining techniques in the diagnosis and prediction of breast cancer and also an analysis of the prediction of survivability rate of breast cancer patients. The data used is the SEER PublicUse Data.
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تاریخ انتشار 2015