Bowel cancer kills thousands each year, and current stool-based screening misses many cases. This PhD develops a new non-invasive method that analyzes human cells shed into stool, aiming to detect normal, pre-cancerous, and cancerous changes more accurately. The goal is a more reliable, higher-participation screening tool that could replace the existing national test.

Mel-AI is an artificial intelligence system designed to assist pathologists in distinguishing melanoma from benign moles. By training computer-vision models on 520 cases, the system reached 96% accuracy and interpretable outputs. It offers scalable, objective quality assurance, reducing misdiagnosis risk and improving melanoma detection in high-incidence countries like Australia.