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A quantitative performance study of two automatic methods for the diagnosis of ovarian cancer.
We present a quantitative study of the performance of two automatic methods for the early detection of ovarian cancer that can exploit longitudinal measurements of multiple biomarkers. The study is carried out for a subset ...
Impact of a decision aid about stratified ovarian cancer risk-management on women's knowledge and intentions: a randomised online experimental survey study.
BACKGROUND: Risk stratification using genetic and other types of personal information could improve current best available approaches to ovarian cancer risk reduction, improving identification of women at increased risk ...
A risk prediction algorithm for ovarian cancer incorporating BRCA1, BRCA2, common alleles and other familial effects.
BACKGROUND: Although BRCA1 and BRCA2 mutations account for only ∼27% of the familial aggregation of ovarian cancer (OvC), no OvC risk prediction model currently exists that considers the effects of BRCA1, BRCA2 and other ...