Validating data-driven population-reference models (Braincharts, Bethlehem et al., Nature, 2022) with neuroimaging and clinical records for disease stratification and prognosis in neurodegenerative cohorts.
This work involves analyzing neuroimaging and clinical data from memory clinics at Addenbrooke’s Hospital and other NHS trusts around the UK, using artificial intelligence (AI) and normative models to develop individualized tools for patient stratification and prognostication in dementia.
The PASSIAN Project focuses on implementing federated learning in the NHS to create a secure, scalable clinical data-sharing solution. This work addresses a critical barrier to developing AI implementations for real-world biomedical data.
Using artificial intelligence (AI) tools in combination with clinical and biological data for individualized dementia diagnosis. This work involves expertise with data-driven approaches to neuroimaging in memory clinic cohorts (QMIN-MC and NACC), including data standardization, preprocessing, and harmonization.