Using Machine Learning to Improve Cancer Outcomes

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Cancer treatments such as radiotherapy deal with many forms of uncertainty in order to deliver appropriate dosage to the disease. Ideally appropriate treatment recommendations are based not only on data from clinical trials but also past histories of similar patients undergoing routine care across multiple cancer care providers. This project will investigate novel machine learning methods of accessing routine clinical data and then quantifying uncertainties and risks from this data and incorporating these into decision support aids in informative ways for radiation oncology. One challenging aspect of this project is that this data is not centralized and therefore the proposed methods will need to operate in an environment where data is distributed across a network of hospitals. The outcomes of this work will impact on future cancer treatments with the potential to expand into other medical areas and other machine learning areas.

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Supervisory team
Geoff
Delaney

Medicine
South Western Sydney Clinical School
Matthew
Field

Medicine
South Western Clinical School
Lois
Holloway

Medicine
South Western Clinical School
Geoff.Delaney@sswahs.nsw.gov.au

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