Development of a novel computational pathology platform to identify bowel cancer patients at risk of relapse

Colorectal cancer, which affects the colon and rectum, is the second worst cancer in Australia. Around 20% of early-stage patients will have their cancer recur after surgery, resulting in a poorer prognosis. Current follow-ups do not accurately predict cancer recurrence. With the rapid growth of artificial intelligence, we can now extract detailed and sub-visual information from clinical records and medical samples. The data is then transformed into a useable dataset. By analysing this dataset, we aim to enhance treatment results, better assess risks, and make more accurate predictions about patient outcomes. We will develop a powerful model to improve decision-making for various treatments and tailor follow-up care for each patient.