Diagnostic Accuracy of Pathologically Confirmed AD in the NACC UDS:
Computational Classification Using Psychometric Measures
 
   Lead Investigator:    Thomas Kiely
   Institution      :    Ray Dolby Brain Health Center/CPMC
   E-Mail           :    kielyt1@sutterhealth.org
   Proposal ID      :    936


   Publications:


1  Moore C, Kiely T, Marreiro C, Lee A, Shaughnessy L, Atri A
   Diagnostic Accuracy of Pathologically Confirmed AD in the NACC UDS
   2017   Abstract  International Neuropsychological Society 45th Annual Meeting   226-227   , 

   PUBLISHED





   Proposal Description:
   Revised diagnostic criteria for Alzheimer?s disease (AD) rely on clinical features, such as patterns of cognitive, behavioral and functional features that can be further supported by biomarker data to improve diagnostic certainty of AD-pathology. In the absence of amyloid/tau biomarkers, 20-33 of patients diagnosed with AD do not have evidence of AD pathology. The inclusion of subjects without AD pathology in AD clinical trials can significantly contribute to failure. This study explores the potential utility of quantitative methods integrating cognitive, functional, and mood factors to improve AD classification accuracy.