Machine-learning approaches to predicting cognitive decline and cognitive impairment in CLSA participants

Changes in cognition are common among aging Canadians and these changes can reflect normal changes in memory or thinking associated with aging processes or may reflect early symptoms of conditions such as Alzheimer’s disease or dementia. There are several common risk factors for cognitive decline in older adults such as age, sex, factors related to individuals social environment, physical and mental health symptoms and the presence of health conditions. Given the range of risk factors that can contribute to cognitive impairment it can be difficult to predict which older adults are at greatest risk of cognitive decline. The Canadian Longitudinal Study on Aging contains detailed information on measures of thinking and memory measured repeatedly over time along with information on common risk factors for cognitive decline. We propose to use computer science methods referred to as machine learning or artificial intelligence to predict cognitive decline or impairment within the CLSA.