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While traditional medical informatics focus primarily on disease classification problems, the disease survivability prediction for patients suffering from multi-stage conditions (e.g., congestive cardiac disorders, cancer types, diabetes, chronic kideny disorder, and so forth) surprisingly remains as an overlooked research topic. In this paper, we address this topic, and among the numerous multi-stage chronic diseases, we select the breast cancer use-case due to the importance of breast cancer patients survivability analysis and prediction for healthcare providers to make informed decisions on recommended treatment pathways for different patients. Then, we combine two main strategies in solving the breast cancer survivability prediction problem using Machine Learning techniques. In the first strategy, we model the survivability prediction task as a two-step problem, namely 1) a classification problem to predict whether …