부산대학교 도서관

Cancer is a complex disease with many distinct forms. Because to its importance in patient care, early cancer research has made prompt identification and management of a cancer type a necessity. When it comes to medical applications, machine learning excels, especially when complicated biochemical and genomics data are involved. As a direct consequence of this, ML is routinely used in the process of diagnosing and detecting cancer. In this paper, the authors proposing a cancer prediction using machine learning algorithms with precedence levels for detection of cervical cancer and breast cancer. After training the basic models, we used ranking-based techniques to forecast final accuracy. The proposed framework is demonstrated by experimental results on two datasets and achieved good accuracy rate for cancer detection.