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Mobile personal health record (mPHR) for Breast Cancer using prediction modeling

The number of cases of cancer in Indonesia is very high. This can be seen from a variety of data published by the government or any cancer research institutes. Cervical cancer has been named as the number one killer of women in Indonesia, followed by breast cancer with an estimated number of 61,682 cases in 2013. This is despite the fact that cancer is a disease that can be cured when detected early, as claimed by an Oncology doctor. Therefore, came the idea of this research with the aim to provide predictive tools of a decision support to assess the level of malignancy of a tumor with a case of data Oncology Hospital Surabaya. In this research, we develop mobile personal health record (mPHR) for Breast Cancer disease using methods in Machine Learning as predictive tools. In this case, Logistic Regression was compared with Naive Bayes method used to predict the risk of of tumor malignancy related to Breast Cancer disease.