%0 Conference Paper
%A Saraiva, João Areias
%A Dyrba, Martin
%A Becker, Martin
%A Krause, Ludwig
%A Berger, Christoph
%A Kirste, Thomas
%A Teipel, Stefan
%T Cross‐Sectional Associations Between the Electroencephalogram and Cognitive Status: Toward Scalable Monitoring Solutions
%J Alzheimer's and dementia
%V 21
%N S2
%@ 1552-5260
%M DZNE-2026-00003
%P e098538
%D 2025
%X Background:Alzheimer's disease (AD) strains healthcare systems in an aging population, emphasizing the need for continuous cognitive decline monitoring and its early detection. The Mini-Mental State Examination (MMSE) remains a widely used and cost-effective diagnostic tool, with efforts underway to adapt it for digital home-based assessments, enabling more frequent monitoring while minimizing patient burden and mobility. Similarly, electroencephalograms (EEG) have been investigated to monitor cognitive status in ambulatory settings. In this cross-sectional study, we identified key EEG features reflecting the cognitive decline process and assessed their feasibility to estimate cognitive status using machine learning (ML).Method:An international and diverse cohort (France, Greece, Turkey, Argentina, Colombia) was gathered comprising N = 510 older adults (40-98 years, 46
%B Alzheimer’s Association International Conference
%C 27 Jul 2025 - 31 Jul 2025, Toronto (Canada)
Y2 27 Jul 2025 - 31 Jul 2025
M2 Toronto, Canada
%F PUB:(DE-HGF)1 ; PUB:(DE-HGF)16
%9 AbstractJournal Article
%R 10.1002/alz70856_098538
%U https://pub.dzne.de/record/283107