Shannon Doyle

PhD Candidate


My background is spread over biomedicine, bioinformatics, entrepreneurship, and AI. As such, I aim to make a positive impact for human health by combining these skills. For this I am well situated in the group ‘AI for oncology’ lead by Jonas Teuwen, where I started my PhD in March 2021. I am also supervised by Hugo Horlings from the Computational Pathology group and Clarisa Sanchez who is a Full Professor for AI in Health at the UvA.

My PhD focuses on the risk and outcome prediction of breast cancer featuring DCIS. Specifically, I am interested to develop deep learning methods to identify calcified lesions with a low harm risk during screening. I will also work on determining which higher-risk (DCIS) lesions are at low risk of progressing into ipsilateral invasive breast cancer based on histopathology data.

  1. J. Minnema, M. van Eijnatten, H. der Sarkissian, S. Doyle, J. Koivisto, J. Wolff, T. Forouzanfar, F. Lucka, K. J. Batenburg, "Efficient high cone-angle artifact reduction in circular cone-beam CT using deep learning with geometry-aware dimension reduction", Physics in Medicine & Biology, 2021-07, 66;(13):135015