"GlioScope was designed to helps doctors identify specific genetic mutations present where there is a brain tumour, but there are currently no good methods for identifying these mutations. Doctors rely on taking samples of brain tissue, which is expensive, slow and carries a high risk of bleeding in the brain. GlioScope allows a doctor to predict what genetic mutation is likely to be present from a simple MRI brain scan, so they can make quicker treatment decisions and reduce risk for the patient."
"Aoibheann has brought together scientific areas of medicine with computer science to improve the chances of early intervention for people with brain cancer. She is a worthy winner of the Stripe Young Scientist and Technologist 2026."
"We started learning about brain tumours, and specifically glioblastoma. And it kind of shook me. It was 2023, and I thought why is the survival rate only 5.1pc, the five-year survival rate?"
GlioScope applies multi-task deep learning and causal AI to profile genetic mutations in glioma and glioblastoma from MRI scans. Current diagnostic methods require tissue samples that are expensive, slow, and carry a high risk of bleeding, forcing reliance on invasive biopsies. Predicting likely mutations from MRI enables faster clinical decision-making, reduced procedural risk, and potential earlier intervention. The project was developed by a 15-year-old student and received the Stripe Young Scientist and Technologist 2026 award in the health and well-being category. The project originated from an early course on brain tumours and concern about low glioblastoma survival rates.
Read at Irish Independent
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