Deep Learning for DNA Methylation-Based Classification and Diagnosis of Glioblastoma Brain Tumours
PhD Project
DNA methylation-based machine learning algorithms are powerful emerging diagnostic tools in tumour classification, offering substantial advancements for brain cancer management. Given the approximately 100 known central nervous system (CNS) tumour types, accurate diagnosis is critical, yet the diagnostic process faces significant challenges, including considerable variability among histopathological interpretations. Recent progress in extracting DNA methylation patterns from tumour tissues, combined with innovations in deep learning and artificial intelligence, provides a unique opportunity to develop highly accurate classification tools, advancing cancer diagnostics.
This research project will leverage publicly available data from international trials to create a comprehensive approach to DNA methylation-based classification specifically for glioblastoma tumours across all entities and age groups. By integrating these data into a robust deep-learning model, this project aims to significantly enhance diagnostic precision over standard methods, ultimately serving as a valuable decision-support tool in neuro-oncology for targeted, personalized treatments.
Desired skills
- Deep learning
- Machine learning
- Artificial Intelligence
- Biomedical Engineering
- Medical Data Analysis
- Bioinformatics
- Neuro-oncology
- DNA methylation
Contact and supervisors
Contact/Main supervisor
Supporting supervisor(s)
- Dr Clinton Turner
- Dr Jason Correia
Page expires: 4 July 2025