Integrating Artificial Intelligence with Biomarkers to Meet the Challenges of Dementia

Dementia, the most common subtype of which is Alzheimer’s disease, represents a significant global and social health challenge. Its effective management is currently hindered by poor access to diagnostic services, a lack of effective treatments and limited post-diagnostic monitoring. This review will explore recent advances in our understanding of key biomarkers underlying the development and progression of Alzheimer’s disease and its associated comorbidities. It will also highlight major data collection efforts in the area and emerging artificial intelligence-based approaches, including imaging, speech, movement, and cognitive data that are being used to improve the risk assessment, diagnosis, and monitoring of Alzheimer’s disease. The development of simple, scalable, and cost-effective artificial intelligence-based tools offers the potential to transform Alzheimer’s disease care through early intervention, more personalised treatment, and improved access to care, offering hope to current and future Alzheimer’s disease sufferers.