Differential Dementia Diagnostics

Proposal details

Title: Using probability indices to identify the underlying cause of dementia producing diseases and disorders
Research Area(s): Brain Modeling
Background: We recently completed a differential dementia study based on autopsy confirmed datasets. Based on this study we were able to use various demographic,clinical, neurodiagnostic and genomic data to generate probability scores in predicting the underlying cause(s) across various dementia producing diseases and disorders. As a continuation of this project we are comparing our data to the datasets available in Brain Net to assess if these additional datasets would enhance the predictive validity of what we have already established. If predictability is enhanced, I would like to incorporate these data into our analysis.
Aims: Improve the differential dementia diagnostic process for clinical research and clinical practice
Method: We will select relevant diagnostic datasets such as Alzheimer's disease, MCI and depression from the Brain Net data from Integ, Web, Lab and MRI Neuro. We will add these data into the probability algorithm we created from autopsy confirmed dementia studies. If the additional Brain Net datasets increase the sensitivity and specificity of the Neurodegnerative Disease Probability Index in Dementia; we would like to incorporate these data into the diagnostic algorithm.