Assessing the Impact of Socio-economic Variables on Breast Cancer Treatment Outcome Disparity

Years of Potential Life Lost Due to Breast and Cervical Cancer: a Challenge for Brazilian Public Policy

“…However other study indentified that African American had statistically worse survival outcome, showing that the race are important determinants of breast cancer outcome (Cheung, 2013). About to marital status, study realized with Indian females about the participation in the breast cancer screening detected that women who were not married were significantly less likely to participate in any level of the screening process than married women (Frie et al, 2013).…”

Black Hispanic and Black Non-Hispanic Breast Cancer Survival Data Analysis with Half-normal Model Application

“…There are several risk factors associated with increased incidence of breast cancer and this includes genetic factors, socio-economic status, education level, race and ethnicity, and access to care (Liu et al, 2012;Cheung, 2013). Age is one of the most predictive factors of breast cancer; as a woman ages, her risk of being diagnosed with breast cancer also increases (Virnig et al, 2010;Van de Water et al, 2012).…”

“…Breast cancer, however, is the second leading cause of death among black and white Hispanic women resulting in 17,100 new invasive breast cancer cases and 2,400 breast cancer deaths in 2012 (Siegel, Naishadham, & Jemal, 2011). Using SEER breast cancer data from 2004 to 2009, Blacks were identified as having the shortest survival outcome of most ethnic and racial groups (Cheung, 2013). In addition, BNH women and Hispanic women, of all races, are less likely than white non-Hispanic women to be diagnosed with early stage breast cancer and BNH women tend to have larger tumors (Ooi et al, 2011;ACS, 2013a).…”

Cancer Prediction Based on Radical Basis Function Neural Network with Particle Swarm Optimization

“…This is a method of computer-aided cancer prediction. The method will 1 greatly reduce the complexity of early preconditioning large amounts of data, improve the accuracy of cancer prediction, and makes the process of cancer prediction more standard (Cheung et al, 2013). At the same time, this approach will liberate people from large amount of data analysis so that they can focus on research to improve the accuracy of cancer prediction, which will greatly improve the efficiency of cancer prediction (Reddy et al, 2012).…”