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Abstract #4125

Diagnostic Decision Support in Alzheimer’s Disease: Predicting Typical and Mixed Forms from Combined Routine Brain Volumetry and Cognitive Assessment

Alexis Roche1,2,3, Daniel Damian4, Frédéric Pedron1, Bénédicte Maréchal1,2,3, Patric Hagmann1, Philippe Maeder1, Reto Meuli1, Tobias Kober1,2,3, and Jean-François Démonet4

1Department of Radiology, CHUV, Lausanne, Switzerland, 2Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland, 3LTS5, EPFL, Lausanne, Switzerland, 4Leenaards Memory Centre, CHUV, Lausanne, Switzerland

We implemented an automated classifier using T1-weighted magnetic resonance imaging-based brain volumetry and the Montreal Cognitive Assessment test to predict whether patients of a University Memory Clinic with suspected neurocognitive disorders have subjective complaints, or suffer from either typical or mixed forms of Alzheimer's disease. The classifier achieved an accuracy of 80.8% and was found to require both psychometric and brain morphometric data to perform best.

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