Dr Sue Astley
University of Manchester
Sue Astley leads research in breast radiomics at the University of Manchester. Her work includes evaluation of novel imaging technologies (CAD, DBT), developing software to detect abnormalities and discover imaging biomarkers, using eye tracking to learn how new imaging systems are best employed, and working closely with radiologists to achieve clinically useful solutions. As breast density lead for the 55,000 strong Predicting Risk of Cancer At Screening (PROCAS) study she has focused her attention on markers of breast cancer risk, harnessing the power of deep learning to exploit the trial data and improve risk prediction.
Deep Learning for Breast Density Assessment and Risk Prediction
I will review the importance of breast density assessment for cancer risk prediction, identifying women for whom mammography is less effective, and assessing the efficacy of risk reducing interventions. I will then discuss current methods for density assessment, looking at the strengths and limitations of different approaches. Finally, I will describe density assessment using convolutional neural networks, including a review of the issues associated with developing and validating such approaches.
EVEN MORE SEMINARS
Professor Paul Leeson University of Oxford
Is AI about to revolutionise cardiovascular ultrasound diagnostics?
Dr Hugh Harvey Kheiron Medical Technologies
Deep Learning in Breast Cancer Screening
Dr Boguslaw Obara Durham University
AI For Healthcare: Case Studies
Baroness Blackwood Department of Health and Social Care
The Government’s approach to AI and ML in Health
Dr Matthew Fenech Future Advocacy
Regulation of AI in healthcare: what should we expect?