Data-driven patient staging
We group patients by stage of disease progression, a step towards individual decisions in research, clinical trials and, in future, clinical practice.
03 · Services
Post-trial services
Data-driven patient staging, prognosis, causal modelling, biomarker integration and brain age.
Machine-learning prognosis
Routinely collected data are used to identify patients at high risk of progression, who may benefit from higher-efficacy treatment, and those with a milder course, who may avoid unnecessary side effects.
Causal modelling
Machine learning applied to trial data to help understand how treatments act in different disorders.
Biomarker integration
Multimodal models that combine MRI, blood biomarkers and other emerging measures, giving a fuller picture of MS and neurodegenerative disease.
Brain age
We estimate brain age from MRI. The gap between estimated brain age and chronological age may help predict disability and treatment response.
Planning a neurology trial?
Tell us about your study and the imaging questions behind it.