Investigating Machine Learning Methods for Detecting Early Dementia

This project, funded by the 'Tri-Faculty Research New Staff Establishment Scheme', addresses the escalating concern of dementia's prevalence among the ageing global population, which imposes substantial financial burdens on both individuals and governments. Given the surge in life expectancy due to advancements in medicine, dementia rates are anticipated to rise correspondingly, underscoring the urgency of early detection, particularly in individuals with mild cognitive impairment at high risk of progressing to dementia.

Our research seeks to conduct a thorough review of the latest methodologies for early dementia detection and to introduce an innovative approach for identifying indicative patterns or symptoms. This approach aims to enhance the ability of caregivers and medical practitioners to respond effectively to emerging health challenges. The efficacy of our proposed method will be assessed using publicly available datasets, and its performance will be benchmarked against leading-edge techniques in the field.