Equity-focused, sex-aware early predictors of dementia by investigating novel multimodal features in the Canadian Longitudinal Study on Aging

Project Summary

Dementia is a growing health concern, affecting hundreds of thousands of Canadians. There is currently no cure for dementia, so finding ways to predict it early and prevent it where possible is crucial. This project will use data from the Canadian Longitudinal Study on Aging (CLSA) to identify potential patterns that predict who is at higher risk of developing dementia in the future, using data science and machine learning (ML) approaches. While traditional studies primarily rely on health records and demographic and lifestyle factors, our approach explores integrating cardiovascular biomarkers captured by ECG as potentially valuable predictors. By analyzing this data, the project aims to discover early warning signs and risk factors for dementia. Identifying such predictors could help doctors and policymakers design better prevention strategies and support for individuals who may be at risk, ultimately contributing to healthier aging in Canada.