PhD Recipient: Max Schuran, Melbourne School of Population and Global Health, University of Melbourne
Supervisors: Professor Enes Makalic (Department of Data Science and AI, Monash University), Dr Gill Dite, Dr Benjamin Goudey, Dr Karen Alpen.
Awarded: $10,000 in GERA’s Grant Round 1 (2025)
About the project: Colorectal cancer (CRC) is a leading cause of cancer-related illness and death worldwide. While polygenic risk scores (PRS) show promise for identifying individuals at higher genetic risk, their predictive performance for CRC remains limited. A key challenge is that most PRSs are developed using European ancestry datasets, reducing their accuracy and applicability across diverse populations.
Max’s PhD project will develop a machine learning–based model for genetic risk prediction, trained on large-scale genomic and phenotypic data from the UK Biobank. By using deep neural networks, the project aims to capture complex, nonlinear relationships across the genome and improve risk prediction, particularly for individuals from underrepresented ancestral groups.
Importantly, the model will be designed to extend beyond colorectal cancer, with potential applications to other complex diseases, including breast cancer. External validation of the model using diverse datasets is also planned to ensure robustness and transferability.
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