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Research projects
Focused scientific study, led by Turing researchers, working with other academics and often industry collaborators, towards defined objectives. Turing research projects aim to be multidisciplinary and multi-institutional, delivering both scientific and real-world impact.
The eye: a window into brain cardiovascular disease
Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease
Future Indonesian Tsunamis: Towards End-to-end Risk quantification (FITTER)
Using high performance computing, uncertainty quantification, and economics to evaluate the risk posed to livelihoods by future tsunamis in Indonesia
Using machine learning to identify patients likely to survive open heart surgery
Developing a new risk calculator using a large dataset from all patients undergoing surgery in the UK
Disease trajectories following a heart attack
Investigating the use of process mining techniques to understand disease pathways amongst 145 million hospitalisation records
Molecular causal networks of hypertension
Using machine learning techniques to investigate causal networks of hypertension at molecular level
Personalising treatment in type 2 diabetes
Developing and testing a decision support tool for primary care to optimise the selection of glucose-lowering therapy for people with type 2 diabetes
Metabolomics networks for medicines testing
Using time dependent and genetically informed causal metabolomics networks for the assessment of medications
Virtualised hardware acceleration for data analytics
Improving performance, efficiency and flexibility of analytics systems
Project FAIR: Framework for responsible adoption of artificial intelligence in the financial services industry
Responsible artificial intelligence in financial services
Project Bluebird: An AI system for air traffic control
Advancing probabilistic machine learning to deliver safer, more efficient, and predictable air traffic control
The SPIRIT-AI and CONSORT-AI initiative
Improving the quality of evidence for AI health interventions
Ethical assurance of digital mental healthcare
A participatory approach to providing ethical assurance of data-driven technologies for mental healthcare
Learning machines – infrastructure for augmented intelligence
Developing infrastructure and methods for supporting continuous use of machine learning algorithms
