Funding Body: Cancer Research UK
Principal Investigator: Dr. Adam Brentnall, Prof. Giovanni Montana,
Breast density (also known as mammographic density) is the amount of white and bright regions seen on a mammogram. High breast density can make it harder for doctors to detect breast cancer on a screening mammogram and also increases the risk of developing breast cancer.
Measuring breast density can become a useful health tool for women, however, the way it is measured still needs to be improved, and it is not clear how best to use the information to aid early detection and prevention of the disease.
Part of this project is framed in this context. We aim at finding more reliable ways of measuring breast density, and at evaluating the risk of not seeing cancer during the screening because of breast density.
The main ingredient of our project is developing AI algorithms to improve the risk assessment of breast cancer. With the increasing availability of medical data, AI has become an evolving trend in the medical field. In preventive health care, the wealth of available data provides opportunities for more accurate health monitoring. The social impact of using AI in healthcare is a complex matter that attracted the attention of governments, media, and society in general.
Our project will develop an artificial intelligence system to design a risk-adapted screening programme, by assessing risk of breast cancer in a mammogram at screening, and the long-term risk of breast cancer following a negative screen by mammography.The three questions we hope to answer are:
The ultimate user of medical AI are patients. Thus the healthy development of AI in healthcare depends, to a certain extent, on researchers being able to understand the public’s views and communicate transparently about their research. This is why it is important to us to discuss with a PPI group about the best ways to communicate about complex artificial intelligence algorithms, and about the inclusion of a component based on artificial intelligence in long-term risk of breast cancer.
Dr. Adam Brentnall
Prof. Giovanni Montana
Dr. Celeste Damiani
Dr. Grigorios Kalliatakis