Anatomical model of a brain
Anatomical model of a brain

Academic Lead: Dr Jorge Cardoso

Clinical Lead: Professor James Teo

Clinical Area: Neurology

Partner: UCL Institute of Neurology

Neurological illnesses are individually as unique as the patients they affect. This is an inevitable consequence of the brain’s extreme complexity.  

Computational constraints have traditionally limited neurology to simple, generic models only weakly predictive of the course and optimal treatment of an individual patient’s illness. For stroke and related disorders this has meant an inability to provide personalised treatment and delayed reaction to patient needs rather than early anticipation of them.  

Our solution is to apply novel machine learning to the rich biological information clinical brain imaging and other tests routinely provide, creating complex models with high individuating power that can be readily deployed within existing healthcare pathways.  Care is thereby personalised, without the burden of new investigations, enhancing its quality while optimising the resources needed to deliver it. Our novel portfolio of technologies, developed to readiness for translation into fully deployable products, will improve clinical outcomes, enhance operational efficiency, and catalyse the development and evaluation of new interventions across healthcare.