Data mining is revolutionizing the early detection and risk assessment of cognitive health conditions, with significant implications for individuals and public health policies. With its ability to analyze extensive datasets, machine learning algorithms are pinpointing subtle signs of cognitive decline and identifying individuals at risk before symptoms arise by examining genetic markers, neuroimaging data, and lifestyle factors. Predictive models are being developed to recommend personalized interventions, helping to delay or prevent the onset of diseases such as dementia. The insights gained from data mining are guiding more effective public health campaigns and resource allocation, aiming to address risk factors for cognitive diseases on a broader scale.