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AI-guided solutions for early detection of neurodegenerative disorders

Artificial Intelligence, Clinical Neurology, Data Science and seminar by Professor Zoe Kourtzi, Department of Psychology, University of Cambridge

Hosted by Cambridge Neuro

Tuesday 16:00–17:10 London (GMT+1)

Recording available

Online

Abstract

Despite the importance of early diagnosis of dementia for prognosis and personalised interventions, we still lack robust tools for predicting individual progression to dementia. We propose a trajectory modelling approach that mines multimodal data from patients at early dementia stages to derive individualised prognostic scores of cognitive decline Our approach has potential to facilitate effective stratification of individuals based on prognostic disease trajectories, reducing patient misclassification with important implications for clinical practice.

Topics

clinical practicedementiaEarly Diagnosismultimodal dataprognostic scores