Nicholas C. Firth

This paper introduces SuStaIn, a machine learning method that identifies disease subtypes and their temporal progression from cross-sectional data, improving prediction of diagnostic conversion in neurodegenerative diseases.

This paper introduces KDEMM for disease progression modeling, showing it outperforms GMMs in simulating cognitive data and aligns better with clinical phenotypes in Alzheimer's subtypes.

This study identifies the sequence of grey matter atrophy progression in multiple sclerosis using longitudinal MRI data and shows its association with disability accumulation in relapsing-remitting MS.

This study uses an event-based model to analyze cognitive decline in adults with Down syndrome, showing similar patterns to Alzheimer's disease and identifying useful measures for tracking decline stages.