Shannon Doyle’s PhD focuses on risk prediction in breast cancer using deep learning. Her current project aims to predict ipsilateral DCIS recurrence from histopathology whole-slide images of excised lesions to reduce the overtreatment of women with radiotherapy.

In her second PhD project, Shannon will predict the risk posed by calcifications in mammography images to reduce the number of unnecessary referrals at breast cancer screening.

Shannon’s main supervisors are Jonas Teuwen, leader of the AI for Oncology group at the Netherlands Cancer institute, and Clarisa Sanchez. Additional supervisors are Jelle Wesseling on the DCIS risk prediction project and Ritse Mann on the calcification risk prediction project.

Prior to her PhD, Shannon worked on a project on artefact removal with image segmentation networks from CBCT images at the CWI (Center for Mathematics and Informatics). Shannon has a Master’s degree in bioinformatics from the University of Amsterdam/Vrije Universiteit and a Bachelor’s degree in Pharmacology from University College London. Additionally, Shannon has experience with entrepreneurship, founding a bioinformatics startup focused on optimising gut health.