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Updated: Mar 2, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Improving the Clinical Recognition of Very Mild Dementia Using Multiple Levels of Assessment
Andreas Ströhle1, A Richert1, H Maier1
1Berlin Memory Clinic, Germany.
Abstract:
Neuropsychological test batteries alone are often unable to differentiate very mild dementia from both normal aging and mild dementia of the Alzheimer type (DAT). The authors hypothesized that some of the difficulties of neuropsychological tests in the identification of very mild dementia could be overcome by the inclusion of additional levels of assessment (activities of daily living, psychopathology, and subjective complaints). Three groups (very mild dementia, mild-to-moderate DAT, and healthy control subjects) of community-dwelling older persons were assessed on cognitive and noncognitive variables. Results indicated that noncognitive variables improved prediction of group assignment. For accurate identification of all patients with very mild dementia, in addition to neuropsychological variables, subjective complaints of impaired orientation and disturbances of apperception were necessary and sufficient.
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