What we do
Using data analysis, simulation, and formal methods to improve diagnosis, monitoring and treatment of patients.
- Simulating the spread of infection.
- Detection and segmentation (highlighting) of cancer in medical images using deep learning (AI). This helps with diagnosis and treatment.
- Measuring people’s vital signs (heart rate and oxygen level) at a distance using cameras and signal processing. Reducing infection risk and measuring multiple people at once.
- Methods to detect and resolve problems in polypharmacy, avoiding inappropriate drug therapies and guaranteeing medication safety.
- Simulating epidemics and disease with complex networks
- Medical Technology
- Medical Image Analysis using Deep Learning
- Security and privacy of healthcare systems
Our Featured Projects this Year
Challenging the ‘Male Default’ Paradigm: Utilising Advanced Data Visualisation to Raise Awareness Gender Bias in Healthcare
This dissertation project, titled ‘Challenging the ‘Male Default’ Paradigm: Utilising Advanced Data Visualisation to Raise Awareness of Gender Bias in Healthcare,’ aims to use innovative data visualisation techniques to shine a spotlight on gender bias in healthcare, enabling a more inclusive and equitable approach to medical decision-making, research, and patient care. The “Male Default” paradigm…
Anonymising medical data for use in machine learning is important to preserve patient privacy and, in many circumstances, is a requirement before data can be made available. One approach to anonymising image data is to train a generative model to produce data that is statistically similar to the input data and use the synthetic data…