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Updated: Jul 26, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Pilot Testing of the MyCog Assessment: Rapid Detection of Cognitive Impairment in Everyday Clinical Settings
Laura M Curtis1, Stephanie Batio1, Julia Yoshino Benavente1
1Northwestern University, Chicago, IL, USA.
Abstract:
Cognitive impairment (CI) and dementia can have profound social and emotional effects on older adults. Early detection of CI is imperative both to the identification of potentially treatable conditions and to provide services to minimize the effects of CI in cases of dementia. While primary care settings are ideal for identifying CI, it frequently goes undetected. We tailored a brief, iPad-based, cognitive assessment (MyCog) for primary care settings and piloted it in a sample of older adults. Eighty participants were recruited from an existing cohort study and completed a brief, in-person interview. CI was determined based on a diagnosis of dementia or CI in their medical record or based on a comprehensive cognitive battery performed within the past 18 months. MyCog had a sensitivity of 79% and specificity of 82%, offering a practical, scalable, primary care assessment for the routine case finding of cognitive impairment and dementia.

