Machine learning model for early dementia risk prediction using common risk factors in primary care settings

The models we developed can function as effective screening tools for estimating the risk of developing dementia 3 to 5 years in the future, utilizing easily accessible features at the GP level. The strength of these models lies in their incorporation of common risk factors that are routinely collected or readily available during standard GP visits. This approach represents a practical and scalable method for the early detection and prevention of dementia. By leveraging readily available data, these models could serve as valuable resources in primary care settings, potentially alleviating the global burden of dementia through timely interventions and personalized risk management strategies. Acknowledgment This Project Is Supported By The Innovative Health Initiative Joint Undertaking (IHIJU) Under Grant Agreement No 101132356. The JU Receives Support From The European Union's Horizon Europe Research And Innovation Programme. This Work Was Funded By UK Research AndInnovation (UKRI) Under The UK Government's Horizon Europe Funding Guarantee [UKRI Reference Number: 10083181]. In Switzerland The University Of Geneva Is Funded For PREDICTOM By The Swiss State Secretariat For Education Research And Innovation (SERI- Ref-1131 52304).