The University of South Australia will lead a world-first study, using artificial intelligence, to map the risks of the most fatal reproductive cancer in women worldwide so it can be detected and treated earlier. Internationally-renowned nutritional epidemiologist Professor Elina Hypponen and a team from UniSA's Australian Centre for Precision Health have been awarded $1.2 million by the Federal Government to map the genetic and physical risks of ovarian cancer, based on the health records of 273,000 women from the UK Biobank database. A machine learning model, which automatically analyses the data to identify patterns of risk, is expected to accurately predict which women will develop ovarian cancer in the next 15 years. Ovarian cancer is usually diagnosed very late due to vague symptoms and few known causes, with a five-year survival rate of less than 30 per cent for women with late-stage cancer. Genes, diet and lifestyle come into play and the researchers say a computational approach will narrow down those most at risk.