AI for Individualized Dementia Diagnosis in Memory Clinics

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.

The project integrates multiple data streams:

• Multimodal neuroimaging (structural MRI, diffusion, functional imaging)
• Clinical assessments and cognitive testing
• Biological markers and biofluid data
• Longitudinal patient trajectories

Key innovations:

• Machine learning models for early dementia detection
• Individualized risk prediction and disease trajectories
• Data harmonization across multiple NHS trusts and research cohorts
• Integration of AI tools into clinical workflows for real-world impact
• Development of interpretable models for clinical decision support

This work aims to bridge the gap between AI research and clinical implementation, providing practical tools for improving dementia diagnosis and patient care in memory clinic settings.