Hadamard Kernel SVM with Applications
摘要
It is a well-established fact that \(13\%\) of deaths worldwide were attributed to cancer [8]. Among women, breast cancer stands out as a leading cause of death globally. Breast cancer claimed 670,000 lives globally in 2022. Approximately half of all breast cancer cases occur in women with no identifiable risk factors other than gender and age. In 2022, breast cancer ranked as the most prevalent cancer among women in 157 out of 185 countries. Notably, breast cancer affects women in every country worldwide. Early detection and diagnosis of breast cancer are essential for minimizing the adverse effects of the disease. On the other hand, cancer prognosis plays a crucial role in designing treatment protocols, which is also of great importance. Cancer prognosis involves estimating the probability of survival within a specific period. A 5-year prognosis of 90% indicates a 90% probability of surviving for 5 years following surgery or diagnosis. Here we formulate the prognosis problem as a classification task, where label information is derived from survival data beyond the prognosis period. For instance, patients who decease before the designated prognosis period are labeled as negative, and vice versa.