Data-driven risk algorithms from primary care for early dementia detection and prevention trial enrichment
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Abstract
Background: Early identification of individuals at risk of dementia is essential for effective prevention and timely intervention. Existing risk scores rely heavily on age, which limits their discriminative power at clinically relevant thresholds such as 65 years, when preventive strategies are most impactful.
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Authors: Thomas Nédelec, Karim Zaidi, Charlotte Montaud, Octave Guinebretiere, Pyry N. Sipilä, Wei Dang, Fen Yang, Yulin Hswen, Fang Fang, Mika Kivimäki, Manon Ansart, Stanley Durrleman
Institutions: Karolinska Institutet, University of Helsinki, Sorbonne Université, Harvard University Press, Université Bourgogne Franche-Comté, Laboratoire de Biologie et Pharmacologie Appliquée, Criteo (France)