A statistical framework for breast-cancer recurrence uses long-term follow-up data and a knowledge of molecular subcategories to model distinct disease stages and to predict the risk of relapse.

An exciting opportunity has arisen for a highly motivated Research Associate to join the Centre for Cancer Genetic Epidemiology (CCGE) at the Department of Public Health & Primary Care, University of

Diagnosing cancer early and accurately is key to improving patient outcome. Here, the authors have developed algorithms to estimate the chances of having a person having an existing, as yet undiagnosed cancer. These algorithms can be used to triage patients for further assessment to improve chances of an earlier diagnosis.

This study develops a semi-supervised classifier integrating multi-genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer....