A multimodal deep learning model to predict individual cancer patient survival probabilities
Dr Colin McLean, Prof J Edwards, Dr P Hall

About the Project
Can a deep learning framework that accommodates complex cancer ‘omics data, such as gene-expression data, with clinical phenotypic data enhance our ability to predict cancer patient survival probabilities?
Deep neural networks are versatile machine learning techniques, which make it possible to build frameworks which learn from multi-modal data that can outperform traditional modelling methods. Such methods require large amounts of data, which has limited their use to date. New data opportunities in Scotland will now enable us to enhance research patient cohorts containing detailed ‘omics data with rich NHS clinical data on patient characteristics, cancer characteristics, treatment information and a range of clinical outcomes. Combining real-world clinical data with existing research data will allow us to address this question, initially with the priority cancer types of colorectal cancer, mesothelioma and ovarian cancer.
Improving our ability to predict disease-specific survival and other relevant patient outcomes using the full breadth of data is important, not only for the discovery and development of novel biomarkers, but also as a tool to help guide clinicians and patients in their choice of treatments and to better understand their prognosis.
This cancer informatics project will lever clinical and biological informatics expertise in Edinburgh and Glasgow to develop and implement the use of deep learning applied to the full breadth of pertinent data.
Application procedure
Up to 4 studentships are available to start in September 2023 for outstanding applicants with a stipend of £21,000 p/a. These 4 STUDENTSHIPS are funded by the CRUK Scotland Centre, a joint initiative between Edinburgh and Glasgow. Successful students for Edinburgh lead projects will be registered for their degree in Edinburgh and will undertake their project in Edinburgh.
Candidates should hold at least an upper second-class degree in a relevant subject and comply with University of Edinburgh English language requirements.
For further information on how to apply, please visit: https://www.ed.ac.uk/cancer-centre/graduate-research-and-training/cancer-research-uk-phd-programme