Data Mining to Reveal Factors Associated with Quality of Life among Jordanian Women with Breast Cancer

Abstract: Globally, breast cancer is a major type of cancer among women. This study focused on identifying factors associated with Quality of life among Jordanian women undergoing breast cancer treatment using data mining. Data mining was used to reveal variables by employing several algorithms and the Support Vector Machine to a secondary data set. The results indicated that the factors most strongly related to the physical well-being were pain and fatigue, in the psychological well-being were fear of metastasis, recurrence, and fear from future diagnostic tests, in the social well-being were cancer effect on the women?s relationship, and household activity, and in the spiritual well-being were feeling of purpose in life and feeling hopeful. The study signaled the importance of using data mining in health-related studies, and it showed that the dimensions of quality of life of breast cancer women are interrelated and cannot be isolated. Therefore, providing of effective individualized holistic care approach for these women provided by a multidisciplinary team may ease the disease trajectory and improve the quality of life of women with breast cancer