Treatments for dementia are starting to come into medical practice but inaccurate diagnosis can result in patients not being given the most appropriate treatment. Current statistics suggest 7% of dementia cases are DLB, but research suggests it could actually be as high as 30%.  

This project will use data science to analyse swathes of patient data to identify who is at greatest risk of the disease. We will do this using clinical records which already exist in the NHS Clinical Record Interactive Search (CRIS), meaning no extra medical examinations or tests are needed for this research. The PhD student will work with clinical researchers, data scientists and statisticians, on this cross-disciplinary project.  

The aim is to create a risk prediction model which will help clinicians to diagnose the disease, and also enable people to be flagged for monitoring, if they’re deemed high risk. Overall, this will result in patients being given the best treatment at the earliest stage, improving patient outcomes for a condition that has a worse prognosis than Alzheimer’s Disease and could be impacting as many as 30% of dementia patients.  

Supervisor: Dr Jay Amin, Associate Professor in Psychiatry of Old Age 

Secondary supervisors: Prof Hajira Dambha-Mille, GP and Associate Professor in Primary Care Research; Professor Simon Fraser, Primary Care Research; and Dr Rebecca Beardmore.