Predicting and characterizing survivability for breast cancer patients
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The negative impact surrounding breast cancer as a disease affecting mainly women has caught the attention of practitioners and researchers around the world. Data mining techniques and health care have been integrated to improve breast cancer prediction in patients. Nonetheless, these models could be improved further by exploring in more detail their structure. Hence, this work's objective is to improve disease's comprehension by modeling survivability's behavior on breast cancer patients and extracting molecular patterns that characterize those with higher risk of dying. The implementation of a multi-step data mining approach for the construction of these models includes an in-depth biological interpretation of important variables.