Multimodal Models Provide Earlier Prediction (10 Years Prior to Diagnosis) of Dementia and Cognitive Decline  and Personalized Actionability for Risk Mitigation for At-Risk Individuals

Current approaches for predicting an individual’s risk of developing dementia rely primarily on single modality data and/or single biomarkers. Here we evaluate the utilization of non-invasive MR imaging and genetics for early detection and prediction of cognitive decline and dementia. We demonstrate superior performance of our multi-measurement, multimodal approach. Moreover, our approach performs as well or better than invasive amyloid PET. We further show a method that identifies modifiable factors upon which an individual can act to mitigate their risk with the long-term goal of empowering high-risk individuals with personalized action plans earlier when the disease progression can be slowed.