Applying under-sampling techniques and cost-sensitive learning methods on risk assessment of breast cancer.

Abstract excerpt

Breast cancer is one of the most common cause of cancer mortality. Early detection through mammography screening could significantly reduce mortality from breast cancer. However, most of screening methods may consume large amount of resources. We propose a computational model, which is solely based on personal health information, for breast cancer risk assessment. Our model can be served as a pre-screening...

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Bayes Theorem
• Share to Body Weights and Measures
• Share to Breast Feeding