Projects

Data-driven models for Progression Of Neurological Disease

Data-driven models for Progression Of Neurological Disease

Neil's UKRI Future Leaders Fellowship

Development and deployment of a deep learning segmentation tool to segment the hippocampus from T1 MRI scans.

Danny's Wellcome Trust Investigator in Science award

A sprint project to break down barriers to AI research on routinely collected healthcare data

Using MRI in late pregnancy to help predict the best mode of birth for an individual mother and baby.

Data-driven disease progression modelling for differential diagnosis of neurodegenerative diseases and their subtypes

Using MRI in late pregnancy to help predict the best mode of birth for an individual mother and baby.

This project uses POND models to analyse autosomal dominant Alzheimer's disease and investigates the relation between disease progression, biomarker evolution, genetic mutation status and cognitive performance. Key outputs include data-driven sequences of disease progression, subtype genetic profiles, cognitive performance trajectories, and early pre-symptomatic biomarkers.