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
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
Related seminars
Machine learning methods applied to dMRI tractography for the study of brain connectivity
Video · 1 h 17 min · Aug 19, 2020Pamela Guevara, Department of Electrical Engineering, Faculty of Engineering, Universidad de Concepción, ChileCNStalk: Using machine learning to predict mental health on the basis of brain, behaviour and environment
Video · 1 h 4 min · Mar 31, 2022Andre Marquand, Donders Institute
More from Cambridge Neuro
All talksImmunosuppression for Parkinson's disease - a new therapeutic strategy?
Video page · May 30, 2023Caroline Williams-GrayFeedback control in the nervous system: from cells and circuits to behaviour
Video page · May 16, 2023Timothy O'LearyTargeting Maladaptive Emotional Memories to Treat Mental Health Disorders: Insights from Rodent Models
Video page · May 9, 2023Amy MiltonFragile minds in a scary world: trauma and post traumatic stress in very young children
Video page · Mar 14, 2023Tim Dalgleish