Deep Reinforcement Learning for Discovering and Visualising Biomarkers

This project will develop novel methods for discovering and visualising optimal biomarkers from chest computed tomography images based on extensions of recently developed deep reinforcement learning techniques. Our project aims to discover previously unknown biomarkers associated with important clinical outcomes. 

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Automated Analysis of Multi-modal Medical Data using Deep Belief Networks

Recently, magnetic resonance and ultrasound imaging have found utility as adjuncts to mammography in the detection and management of breast cancer. This project will develop novel machine learning techniques that optimally integrate information from each of these data sources so as to improve the efficiency and accuracy of breast cancer diagnosis.

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